Pulse Code Modulation

Tässä insinöörityössä kehitettiin National Instrumentsin ultraäänisensorilla varustettua robottia. Sen ensimmäistä langatonta versiota kehitettiin vuonna 2012 Metropolia Ammattikorkeakoulun innovaatioprojektina. Innovaatioprojektissa robotti saatiin toimimaan langattomasti tietokoneen välityksellä, mutta kännykällä toimivan kokoonpanon ohjaus osoittautui tuolloin haasteelliseksi. Tämän insinöörityön tavoitteeksi asetettiin täysin langaton kommunikointi robotin ja kännykän välille. Työn toteutukseen tarvittiin MBED-mikrokontrollerimoduuli ja langaton WLAN-moduuli, jotka liitettiin suoraan robotin piirikorttiin kiinni. Ohjausdatan välittämiseksi moduulille pohdittiin erilaisia ratkaisuja. Työssä selvitettiin robotin piirikortin sekä lisätyn mikrokontrollerimoduulin tukemia yhteyskäytäntöjä ja valittiin niistä sopiva vaihtoehto. Robottiin lisättyyn MBED-mikrokontrollerimoduuliin toteutettiin sisäinen http-palvelin toisen Metropolia Ammattikorkeakoulun opiskelijan insinöörityönä. Sisäis...

Methods ot retrieval ot signiticant intormation in biomedical curves, based on the application ot the algorithms ot data compression , are described. These methods employ the a priori intormation about the morphology ot the type ot the curve under examination, emphasizing the standpoint ot the user. -The identitication ot the characteristic points and ot the intormative sections ot biomedical curves is paid closer attention. The procedure is illustrated by two actual algorithms, applied to the analysis ot ECG and EMG signals.

This study is to improve image data compression performance based on variable block-size quadtree image segmentation applied to double predictor differential pulse code modulation (DP-DPCM) image compressive algorithm. The quadtree segmentation method is applied to better allocate image characteristics. A variable block-size double predictor DPCM (VBDP-DPCM) image coding system works on an image been preprocessed into segments of variable size, square blocks, and each block is separately encoded by a DP-DPCM algorithm. Quadtree segmentation method is utilized to divide a given real-world image into variable size image blocks. The detail regions comprise more image features of a given image is segmented into blocks with smaller block size, and the background regions of the image will be assigned larger block size to the image blocks. After quadtree segmentation process, the average dissimilar values between the nearby pixels within an image block are abridged. Therefore, we can decrease the distribution range of the prediction error anddiminish the quantization levels as well as the coding bit rate. We then adopt the double predictor DPCM technique to moderate the effect from the fed-back quantization error and not to augment the system complexity. The compression performance of this proposed method is about 5dB (or greater) coding gain in Signal-to-Noise Ratio (SNR) than that of a conventional DPCM system.

The problem of distortion accumulation due to tandem transcodings in a digital network arises when high-quality, low-rate quantizers (codecs) are introduced into the network. An important class of codecs is vector quantization, which is gaining popularity as a high-performance quantization technique with possible applications in speech and image coding. In this paper, we provide novel transcoding algorithms that eliminate distortion accumulation due to tandem transcodings between memoryless, finite-state, and predictive vector quantization and PCM. These algorithms can be implemented via table lookups for memoryless and finite-state vector quantization, whereas predictive vector quantization requires online calculations. Codecs designed using these algorithms could find applications in corporate T1 networks or mobile communication systems, where several tandem encodingldecoding operations on voice signals are a common occurrence. Those techniques would also be appropriate for video transcoding in broadband systems, where the transmission rates might be different in local area networks and broadband ISDN backbone networks.

This paper comprehensively reviews the use of phase change materials (PCMs) as latent heat storage systems to improve the productivity of solar stills. Previous studies on enhancing the productivity of active and passive solar stills with PCM are also presented. These studies show that a passive solar still with PCM shows a productivity improvement of up to 120% compared with a solar still without PCM. Meanwhile, the productivity improvement of an active solar still with PCM could reach as high as 700%. These results indicate that productivity increases along with an increasing PCM mass and a decreasing saline water mass. The PCM is also observed to be less effective in daytime than in night-time. It is also shown that organic PCMs (such as paraffin) were mostly used in studies on productivity improvement, whilst very few studies have examined the effects of inorganic and eutectic types of PCM.

Puji dan syukur kami panjatkan kepada Tuhan Yang Maha Esa atas selesainya makalah yang berjudul "PCM (Pulse Code Modulation) Dan Delta Modulation". Kami ucapkan terima kasih kepada semua pihak yang telah membantu dalam proses penyusunan makalah ini. Makalah ini disusun untuk memenuhi tugas mata kuliah Sistem Telekomunikasi. Kami menyadari bahwa makalah ini belumlah sempurna. Oleh karena itu, saran dan kritik yang membangun dari rekan-rekan sangat dibutuhkan untuk penyempurnaan makalah ini.

Page 1. Novel Algorithms for Optimal Compression Using Classification Metrics Bei Xie and Tamal Bose Erzsebet Merenyi Wireless ( Virginia Tech Electrical and Computer Engineering Bradley Department of Electrical and Computer Engineering Rice University ...

Scalable video coding is a technique which allows a compressed video stream to be decoded in several different ways. This ability allows a user to adaptively recover a specific version of a video depending on its own requirements. Video sequences have temporal, spatial and quality scalabilities. In this work we introduce a novel fully scalable video codec. It is based on a motion-compensated temporal filtering (MCTF) of the video sequences and it uses some of the basic elements of JPEG 2000. This paper describes several specific proposals for video on demand and video-conferencing applications over non-reliable packet-switching data networks.

Scalable video coding is a technique which allows a compressed video stream to be decoded in several different ways. This ability allows a user to adaptively recover a specific version of a video depending on its own requirements. Video sequences have temporal, spatial and quality scalabilities. In this work we introduce a novel fully scalable video codec. It is based on a motion-compensated temporal filtering (MCTF) of the video sequences and it uses some of the basic elements of JPEG 2000. This paper describes several specific proposals for video on demand and video-conferencing applications over non-reliable packet-switching data networks.

In this article, a new method for segmentation and restoration of images on two-dimensional surfaces is given. Active contour models for image segmentation are extended to images on surfaces. The evolving curves on the surfaces are mathematically described using a parametric approach. For image restoration, a diffusion equation with Neumann boundary conditions is solved in a postprocessing step in the individual regions. Numerical schemes are presented which allow to efficiently compute segmentations and denoised versions of images on surfaces. Also topology changes of the evolving curves are detected and performed using a fast subroutine. Finally, several experiments are presented where the developed methods are applied on different artificial and real images defined on different surfaces.

In this paper, we propose a novel distributed digital transmission framework for two jointly sparse correlated signals. First, the non-zero coefficients of each signal are quantized by a standard quantizer or a novel distributed quantizer, as appropriate. Then, these quantized values are mapped to the elements of a finite field, except 0, while the zero coefficients are mapped to 0. Subsequently, compressed sensing over finite fields is applied to obtain measurements. We name such an order "first quantization, then compressed sensing." The two measurement signals are then converted to bit sequences, modulated, and transmitted through separate Additive White Gaussian Noise (AWGN) channels. At the central receiver, which has access to both channels, following demodulation, an innovative joint belief propagation (JBP) algorithm is performed for joint recovery. In this algorithm, we introduce a new type of constraint node, i.e., correlation constraint nodes, which connect two factor graphs that separately represent the CS encoding matrix of each signal. Experimental results prove that under the same framework the proposed scheme provides significant performance improvements compared to the scheme that ignores the correlated information between jointly sparse signals, especially when the correlation coefficient is high. Then, to answer the question of which order is better, we construct the "first compressed sensing, then quantization" framework and, for fairness, two cutting edge jointly greedy pursuit algorithms are separately adopted at the joint decoder. Through simulations, we validate that the proposed framework provides more effective and robust transmissions. INDEX TERMS Jointly sparse signals, joint belief propagation, distributed quantizer, distributed compressed sensing, LDPC matrix

This paper discusses the systematization effort undertaken to generate an equipment specification of an extremely detailed and new nature for DCMEs in accordance with the INTELSAT specification IESS‐501. The main areas of importance addressed are additional to what has already been defined within the IESS‐501. A discussion of important aspects when introducing DCME into actual network conditions is also contained and results based on simulations of performance under simulated network environments are included.

Robustness of the differential pulse code modulation system with the first and second order predictor is considered in this paper. Special focus is on a robust stability of prediction filter with regard to predictor coefficients. Generalization of robustness in classical sense is performed and suitable relations for calculating probability of robustness are derived. The proposed method for robustness estimation is used for the first and second order prediction filters in the case of speech signal.

This paper presents the stability analysis of the linear recursive (prediction) filters with higher-order predictors in a DPCM (differential pulse-code modulation) system, where traditional methods become too difficult and complex. Stability conditions for the third-and fourth-order predictor are given by using the Schur-Cohn stability criterion. The probability of stability estimation is performed by using the Monte Carlo method. Verification of the proposed method is performed for lower-order predictors (the first-and second-order). We calculated numerical values of the probability of stability for higher-order predictors and previously experimentally obtained parameters. With large enough number of trials (samples) in Monte Carlo simulation, we reach the desired accuracy.

Robustness of the differential pulse code modulation system with the first and second order predictor is considered in this paper. Special focus is on a robust stability of prediction filter with regard to predictor coefficients. Generalization of robustness in classical sense is performed and suitable relations for calculating probability of robustness are derived. The proposed method for robustness estimation is used for the first and second order prediction filters in the case of speech signal.

Sensitivity analysis of the recursive filter in a DPCM system, with arbitrary order predictor, is presented in this paper. Relations for sensitivity, related to predictor coefficients, are derived both in cases of stable and unstable systems. In this way, we presented new information which can improve design of the system in the sense of better performances via parameters (coefficient) adjustment. Given relations were verified for the case of real system in three different configurations: with the second, third and fifth order predictors.

This paper describes a companded analog-to-digital (A/D) converter for voiceband signals that is simple and potentially inexpensive. The converter uses only 18 coarsely spaced analog levels. Fine resolution is obtained by oscillating between these levels at an increased speed and averaging the result over a Nyquist interval. The companding used in the converter is effectively the same as that of M-255 pulse-code modulation (PCM). In the encoding process a one-bit code is generated at 256 000 sam-ple&. This 1-bit per sample signal can be transmitted and decoded directly, or a simple digital circuit will produce a 13-bit, 8-kHz linear PCM signal that can be compressed to 8-bit companded PCM format. In this paper the basic operation of the 1-bit coder is described and its performance when connected to a 1-bit decoder is illustrated. Methods for obtaining both linear and compressed PCMare then presented, and the properties of these PCY signals with respect to noise, gain tracking, and harmonic content are described. Relative insensitivity to circuit component variations, absence of analog gates, along with the need to generate only a few analog levels, make the coder especially well suited to integrated circuit realization.

Markov-ketjut ovat tärkeä luokka stokastisia prosesseja. Niitä voidaan käyttää mallintamaan prosesseja, jotka toteuttavat Markov-ominaisuuden, jolla tarkoitetaan, että ketjun tulevaisuuden tila riippuu vain sen nykyisestä tilasta. Markov-ketju määritellään sen tilajakauman, ketjun nykytilan ja siirtymämatriisin avulla. Siirtymämatriisi muodostuu ketjun siirtymätodennäköisyyksistä. Siirtymämatriisi voidaan myös esittää siirtymäkaaviona. Useamman askeleen siirtymätodennäköisyydet saadaan laskettua ketjun alkujakauman ja siirtymämatriisin avulla. Markov-ketjun tilat voidaan jakaa yhteysluokkiin niiden kommunikoivuuden perusteella. Jos tilajoukon kaikki tilat kommunikoivat keskenään, sanotaan siirtymämatriisin ja sitä vastaavan Markov-ketjun olevan yhtenäinen. Luokan sanotaan olevan suljettu, jos sen tiloista ei voida päätyä muihin tiloihin. Tila on absorboiva, jos se muodostaa yksinään suljetun luokan. Tilat ja luokat luokitellaan myös palautuviksi ja väistyviksi. Tilan jakso on suurin...

This study is to improve image data compression performance based on variable block-size quadtree image segmentation applied to double predictor differential pulse code modulation (DP-DPCM) image compressive algorithm. The quadtree segmentation method is applied to better allocate image characteristics. A variable block-size double predictor DPCM (VBDP-DPCM) image coding system works on an image been preprocessed into segments of variable size, square blocks, and each block is separately encoded by a DP-DPCM algorithm. Quadtree segmentation method is utilized to divide a given real-world image into variable size image blocks. The detail regions comprise more image features of a given image is segmented into blocks with smaller block size, and the background regions of the image will be assigned larger block size to the image blocks. After quadtree segmentation process, the average dissimilar values between the nearby pixels within an image block are abridged. Therefore, we can decrease the distribution range of the prediction error anddiminish the quantization levels as well as the coding bit rate. We then adopt the double predictor DPCM technique to moderate the effect from the fed-back quantization error and not to augment the system complexity. The compression performance of this proposed method is about 5dB (or greater) coding gain in Signal-to-Noise Ratio (SNR) than that of a conventional DPCM system.

The purpose of this article is to give an overview of the theory of the normal cycle and to show how to use it to define a curvature measures on singular surfaces embedded in an (oriented) Euclidean space E 3. In particular, we will introduce the notion of asymptotic cone associated to a Borel subset of E 3 , generalizing the asymptotic directions defined at each point of a smooth surface. For simplicity, we restrict our singular subsets to polyhedra of the 3-dimensional Euclidean space E 3. The coherence of the theory lies in a convergence theorem: If a sequence of polyhedra (Pn) tends (for a suitable topology) to a smooth surface S, then the sequence of curvature measures of (Pn) tends to the curvature measures of S. Details on the first part of these pages can be found in [6].

This paper describes a Carrier Aiding technique which employs cascaded pha.selockcd loops. This scheme can be useful when two unequal antennas are required to coherently demodulate the received signal, but due to an extremely weak signal-toratio. (SN R) level and high Doppler rates, the snlaller antenna is unable to lock on the carrier on its own. In order to determine the performance for a bank of (L-1) antennas when each one of them is aided by a single larger antenna, the joint pdf of the two cascaded phase error processes for these (L-1) pairs must be determined. These joint pdfs M well as the carrier loop SNRs of the aided antennas are derived based on Fokkcr-Pla.nck techniques. The tracking and acquisition results are verified by si]uulation for the case IJ = 2.

The performance of deep-space telemetry signals that employ a residual carrier modulation technique is compared in the presence and absence of a subcarrier. When the subcarrier is present, the performance for the resulting pulse-coded modulatiodphase-shift keydphase-modulated (PCM/PSK/PM) scheme is evaluated for both sine-wave and square-wave subcarriers and non-return-to zero (NRZ) data. When the subcarrier is absent, the performance for the resulting PCM/PM technique is evaluated for both the NRZ and the bi-phase data format. The comparison is based on telemetry performance as well as bandwidth efficiency. The first criterion is characterized in terms of the symbol error rate (SER) as a function of symbol SNR, loop bandwidth-to-data rate ratio, and modulation index. The bandwidth efficiency is characterized by the occupancy factor. The results of both the analysis and measurements show that when the interference-to-carrier ratio (ICR) is less than-20 dB, the performance degradation in the absence of a subcarrier is negligible. Various combinations of loop bandwidth-to-data rate ratios and modulation indices that achieve this performance are derived and Listed. Bandwidth occupancy comparison indicates that PCM/PM/NRZ is the most efficient in this regard. Therefore, by eliminating the subcarrier and using the PCM/PM/NRZ scheme, many advantages can be realized without any sacrifice in performance.

Muscle activity produces an electrical signal termed the myo-electric signal (MES). The MES is a useful clinical tool, used in diagnostics and rehabilitation. This signal is typically stored in 2 bytes as 12-bit data, sampled at 3 kHz, resulting in a 6 kbyte sstorage requirement. Processing MES data requires large bit manipulations and heavy memory storage requirements. Adaptive differential pulse code modulation (ADPCM) is a popular and successful compression technique for speech. Its application to MES would reduce 12-bit data to a 4-bit representation, providing a 3:1 compression. As, in most practical applications, memory is organised in bytes, the realisable compression is 4 : 1, as pairs of data can be stored in a single byte. The performance of the ADPCM compression technique, using a real-time system at 1 kHz, 2 kHz and 4 kHz sampling rates, is evaluated. The data used include MES from both isometric and dynamic contractions. The percent residual difference (PFtD) between an unprocessed and processed MES is used as a performance measure. Errors in computed parameters, such as median frequency and variance, which are used in clinical diagnostics, and waveform features employed in prosthetic control are also used to evaluate the system. The results of the study demonstrate that the ADPCM compression technique is an excellent solution for relieving the data storage requirements of MES both in isometric and dynamic situations.

Compression of images is of great interest in applications where efficiency with respect to data storage or transmission bandwidth is sought.The rapid growth of social media and digital networks have given rise to huge amount of image data being accessed and exchanged daily. However, the larger the image size, the longer it takes to transmit and archive. In other words, high quality images require huge amount of transmission bandwidth and storage space. Suitable image compression can help in reducing the image size and improving transmission speed. Lossless image compression is especially crucial in fields such as remote sensing healthcare network, security and military applications as the quality of images needs to be maintained to avoid any errors during analysis or diagnosis. In this paper, a hybrid prediction lossless image compression algorithm is proposed to address these issues. The algorithm is achieved by combining predictive Differential Pulse Code Modulation (DPCM) and In...

Salah satu dari teknologi dasar sistem telekomunikasi digital adalah teknik modulasi digital, dimana teknik modulasi digital ini mengizinkan data digital untuk dibawa atau dipancarkan melalui saluran analog frekuensi radio. PCM berfungsi untuk mengubah sinyal analog menjadi digital. Dimana dalam sistem digital, sinyal analog yang dikirimkan cukup dengan sampel-sampelnya saja. Tahap awal dari proses perubah analog ke digital adalah PAM, yang merupakan saklar elektronik yang dikontrol oleh pulsa train (pulsa sampling). Namun, PAM adalah dasar dari metode pengkodean analog-ke-digital. yang penting yang disebut modulasi kode pulsa (PCM). Maka frekuensi dari hasil pengujian tegangan pada osiloskop sebesar 40 Volt dan PCM sebesar 25 volt dengan masing-masing frekuesi sebesar 50 Hz dan PCM sebesar 8 Hz.

The recently introduced unlimited sampling theorem proves that a one-dimensional bandlimited function can be perfectly recovered from a constant factor oversampling of its modulo samples. The advantage of this approach is that arbitrary high-dynamic-range signals can be recovered without sensor saturation or clipping. In this paper, we prove a multidimensional version of the unlimited sampling theorem that works with arbitrary sampling lattices. We also present a geometrical perspective on the emerging class of modulo sampling problem that is based on the topology of quotient spaces.

A new algorithm for lossless compression of hyperspectral imagery is proposed. First, the average value of four neighbour pixels of the current pixel is calculated as local mean, which is subtracted by the current pixel to eliminate correlation in the current band image. The residual produced by this step is called local difference. The local differences of the pixels which co-locate with the current pixel in previous bands form the input vector of the recursive least square (RLS) filter, by which the prediction value of the current local difference is produced. Then, the prediction residual is sent to the adaptive arithmetic encoder. Experiment results show that the proposed algorithm produces state-of-the-art performance with relatively low complexity, and it is suitable for real-time compression on satellites. Introduction: Hyperspectral imagery produced by imaging instruments on the satellite contains abundant information of the Earth's surface, which leads to overwhelming storage and transmission bandwidth. Compression technology is an efficient solution for those problems. Lossless compression is mandatory in many situations, because hyperspectral imagery is analysed not only by human visual systems, but also by mechanical algorithms. Conventional lossless compression algorithms for red-green-blue images, such as JPEG-lossless (LS) [1], can be applied for hyperspectral imagery. However, these algorithms do not exploit the correlations in the bands of hyperspectral imagery. One of the mentioned algorithms in [2], Diff.JPEG, extends JPEG by applying inter-band prediction between two adjacent bands. Some algorithms exploit the multidimensional property of hyperspectral imagery. In [3], the algorithm called clustered-differential pulse code modulation (C-DPCM) clusters the imagery firstly, and then carries out linear prediction. This algorithm generates a very high compression ratio. However, the cluster step is time-consuming, and this algorithm is too complex for real-time applications. A series of algorithms are put forward in [4] based-on look-up tables (LUTs), which can generate good performance with very low complexity. The performances of LUT-type algorithms for the uncalibrated image are inferior to the fast lossless (FL) algorithm proposed in [2], which has been adopted as the recommended standard of the Consultative Committee for Space Data Systems (CCSDS) for onboard real-time compression of hyperspectral imagery [5]. The FL has significantly lower complexity than IP-3 proposed in [6], although the performance of FL is no better than that of IP-3. In this Letter, we propose a lossless compression algorithm based on a recursive least squares (RLS) filter, which generates state-of-the-art performance with relatively low complexity.

A discrete version of the Ricci flow, applicable to images, is introduced and applied in image denoising and in singleimage-based enhancement and super-resolution. This flow is unique among the geometric flows that have been applied in image processing, in that it is the only flow wherein the metric of an image evolves rather than the image itself as is the case in other geometric flows applicable in image processing. The flow is based on the combinatorial Ricci curvature defined by Forman, that was previously introduced by the authors in the context of image processing. It is shown that the Ricci flow preserves image structure much better than the Beltrami flow and other state-of-the-art image enhancement schemes. Implementation of the Ricci flow is applicable also to general surfaces such as required in computer graphics and other applications.

Relationships that exist between the classical, Shannontype, and geometric-based approaches to sampling are investigated. Some aspects of coding and communication through a Gaussian channel are considered. In particular, a constructive method to determine the quantizing dimension in Zador's theorem is provided. A geometric version of Shannon's Second Theorem is introduced. Applications to Pulse Code Modulation and Vector Quantization of Images are addressed.

Nowadays, still images are used everywhere in the digital world. Images take lot of computer space, in many practical situations, all original images cannot be stored, and a compression must be used. Moreover, in many such situations, compression ratio provided by even the best lossless compression is not sufficient, so lossy compression is used. In this paper ,Differential pulse code modulation (DPCM) in slantlet transform and Run Length Code for image compression is used. Apply slantlet transform on each component in the color image(after applying color space conversion from RGB to YCbCr)and encoding Y component by DPCM and encoding Cb and Cr with RLC.The compression ratio and Peak Signal to Noise Ratio (PSNR) are used as measurement tools. When comparing the proposed approach with other compression methods Good result obtained.

Tekijä(t) Otsikko Sivumäärä Aika Timo Pudas Metropolian Virtuoso-robottikäden elektroniikkasuunnittelu ja ohjelmointi 36 sivua + 4 liitettä 11.1.2015 Tutkinto Insinööri (AMK) Koulutusohjelma Automaatiotekniikka Suuntautumisvaihtoehto Automaation tietotekniikka Ohjaaja(t) Teknologiajohtaja Sami Kalliokoski Lehtori Antti Liljaniemi Tämän opinnäytetyön aiheena on Metropolian Virtuoso-robottikäden elektroniikkasuunnittelu ja ohjelmointi. Kyseessä on pienikokoinen ja monipuolinen robottikäsi, jota pystytään ohjaamaan sekä USB-että Ethernet-väylien kautta. Tavoitteena oli saada aikaiseksi mahdollisimman edullinen, alle tuhannen euron hintainen, robottikäsi käyttämällä 3D-printattuja osia sekä edullisia moottoreita ja komponentteja. Työn toteutukseen käytettiin Arduino Mega 2560 R3-kehitysalustaa, Ethernet-shieldiä, sekä itse suunniteltua piirilevyä, joka sisältää moottorinohjaimia DC-moottoreita varten, jänniteregulaattorin, liitännät kehitysalustalle ja moottoreille sekä tarvittavat alasvetovastukset. Moottoreina käytettiin sekä servo-että DC-moottoreita. Robottikäden ohjelma kirjoitettiin Arduino IDE-ohjelmointiympäristöllä. Ethernetkommunikaation testaamista varten kirjoitettiin Processing-kielinen apuohjelma, jolla voitiin lähettää robottikädelle komentoja UDP-paketteina. Työn tuloksena valmistui toimiva ohjelmoinnin opetukseen soveltuva robottikäden prototyyppi. Hintatavoitteeseen päästiin, mutta edullisten moottoreiden ja komponenttien käytöstä syntynyt säästö syntyi toimintatarkkuuden kustannuksella. Sitä voidaan parantaa tulevaisuudessa lisäämällä robottikäden anturointia.

A DPCM system employing a median predictor, which is c:illcd tlic predictive mcdi;in-DPCM(PM~DPCM), is proposed. An interesting property that in PM-DPCM transmission noise is often isolated and not propagated ovci-tlic reconstructed signals i s ohser\,cd ancl is analy/.cd dctci-ministically and statistically. In order to examine tlic pcrlomiancc charactclistics of the PM-DPCM, it is applied to i-cal imigc signals. The cxpciiiiicntal rcs~ilts indicate that the PM-DPCM outperforms the standard DPCM when transmission errors occur, and that tlic fcirmcr pcrfolins like tlic latter iinilcr noise-free conditions.

The discrete cosine transform (DCT) has been shown as an optimum encoder for sharp edges in an image (Andrew and Ogunbona, 1997). A conventional lossless coder employing differential pulse code modulation (DPCM) suffers from significant deficiencies in regions of discontinuity, because the simple model cannot capture the edge information. This problem can be partially solved by partitioning the image into blocks that are supposedly statistically stationary. A hybrid lossless adaptive DPCM (ADPCM)/DCT coder is presented, in which the edge blocks are encoded with DCT, and ADPCM is used for the non-edge blocks. The proposed scheme divides each input image into small blocks and classifies them, using shape vector quantisation (VQ), as either edge or smooth. The edge blocks are further vector quantised, and the side information of the coefficient matrix is saved through the shape-VQ index. Evaluation of the compression performance of the proposed method reveals its superiority over other lossless coders.

Background: Image compression is an area of research that has many applications spanning different technological fields; among the most important of these fields is that of mammography images compression. With whole mammography images becoming increasingly practical and cost-effective, the need for a superior space-saving algorithm is obvious. Also, it becomes important that reconstructed image achieves high compression rates without any alterations from its original form in order to maintain the image quality which has an influence on the accuracy of radiologist diagnosis. Methods: This paper presents a lossless compression algorithm that is based on image enhancement, Haar wavelet transform and differential Pulse Code Modulation (DPCM) to optimize the compression of 50 mammography images. Image enchantment is implemented by two techniques; Histogram Equalization (HE) and top-hat filtering. The performance of compressed images is measured by Compression Ratio (CR), Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and time consumption. Results: This proposed algorithm is compared to existing ones and the results show that the compression ratio has increased from 6.44 to 26.841.

A variable-length packetization process is proposed for logarithmic Pulse Code Modulation (log-PCM)-encoded speech signals. Blocks of W log-PCM words are reduced in size by discarding words on the basis that the receiver can recover the speech with a signal-to-noise ratio (s/n) that is, in general, above a specified value. Specifically, blocks of two hundred fifty-six, 8-bit, μ-law PCM words are left unchanged or reduced to either 214, 205, 192,171, or 128 words. These blocks are then formulated into packets. The discarded samples at the dispatching terminal are replaced at the receiver by means of adaptive interpolation. We found that by specifying the s/n of the decoded speech in each variable-length packet to be above 27 dB, the reduction in the transmitted speech data was 25 percent, while the recovered speech signal had negligible perceptual degradation.

A broad spectrum of techniques for electrocardiogram (ECG) data compression have been proposed during the last three decades. Such techniques have been vital in reducing the digital ECG data volume for storage and transmission. These techniques are essential to a wide variety of applications ranging from diagnostic to ambulatory ECG's. Due to the diverse procedures that have been employed, comparison of ECG compression methods is a major problem. Present evaluation methods preclude any direct comparison among existing ECG compression techniques. The main purpose of this paper is to address this issue and to establish a unified view of ECG compression techniques. ECG data compression schemes are presented in two major groups: direct data compression and transformation methods. The direct data compression techniques are: ECG differential pulse code modulation and entropy coding, AZTEC, Turning-point, CORTES, Fan and SAPA algorithms, peak-picking, and cycle-to-cycle compression methods. The transformation methods briefly presented, include: Fourier, Walsh, and K-L transforms. The theoretical basis behind the direct ECG data compression schemes are presented and classified into three categories: tolerance-comparison compression, differential pulse code modulation (DPCM), and entropy coding methods. The paper concludes with the presentation of a framework for evaluation and comparison of ECG compression schemes.

Compression of highly correlated measurement signals is considered using DPCM/ADPCM (Difference Pulse Code Modulation/Adaptive Difference Pulse Code Modulation) technique. It is important since very often transmission and storage of measurement signals are needed. Theory is applied on ECG (Electrocardiogram) signal, as an example of highly correlated signals. Very good performances are achieved: high compression rate and high improvement of performances are obtained.

Stream is a European Telecommunication standard for communication of daralwoice channels in a digital nehvork. This poper will deal with the design and implementation of0 tramparent stream analper, capoble ofhandling (up to 2 Mbps) E l stream and analyzing 30 wice /data channels using an out-oflband Conpzon Channel S i p l i n g System number 7 (CCSS7) protocol. The analper is capable of generating an El sfread and thus can be used for generarion, monitoring and blocking of channels. The Analyzer can perform analysis and maintenance ofEl (Z.048Mbps) lines. As our a d p e r performs the analysisfinctions in the sofiare it is very flexible and can perform many odditional fiatures such as algorifhm and protocols testing and analysis. The workable synchronous Finite Stare Machine (FSM) design ofanalyzer is implemented in Verilog and verified on Altera P FLEXIOK70 FPGA along with its subsequent interfaEing with PC through Enhanced Parallel Port.

Tässä työssä esiteltiin Roadscanners Oy:n yleisimmin käytössä olevia pintaa rikkomattomia tutkimusmenetelmiä. Pintaa rikkomattomia menetelmiä käytetään yleisesti väylien rakenteellisen ja toiminnallisen kunnon kartoituksissa. Lisäksi menetelmiä hyödyn-netään laadunvalvonnan työkaluina. Työssä tarkasteltiin maatutkausta, pudotuspainolai-temittausta, laserkeilausta ja palvelutasomittauksia. Lisäksi työssä käsiteltiin yleisellä tasolla visuaalisia tutkimusmenetelmiä kuten lämpökamerakuvausta. Työhön valittiin kolme projektiesimerkkiä, joiden kautta perehdyttiin tarkemmin mittausprosessiin ja mittauksista saataviin tulosteisiin. Projekteista hankittiin tietoa Roadscanners Oy:n arkistoista sekä haastattelemalla projekteihin osallistuneita työntekijöitä. Hankittujen tietojen avulla pystyttiin lukijalle selvittämään konkreettisten esimerkkien kautta mittauksista saatujen tulosten sisältöä. Mittausmenetelmien kuvauksia varten tietoa kerättiin erilaisista kirjallisuuslähteistä. Työn tuloksen...

In this paper, real-coded genetic algorithm (GA) is used for designing two-channel quadrature mirror filter (QMF) banks based on the Kaiser Window. The shape of the Kaiser window and the cutoff frequency of the prototype filter are optimized using a simple GA. The optimized QMF banks are exploited as mother wavelets for speech compression based on discret wavelet transform (DWT). The simulation results show the efficiency of the GA for designing QMF banks using adjustable windows length and especially for optimizing wavelet filters used in speech compression based on wavelets. In addition, a comparative of performance of the developed wavelets filters using GA and others known wavelets is made in term of objective criteria (CR, SNR, PSNR, and NRMSE). The simulation results show that the optimized wavelets filters outperform others wavelets already exist used for speech compression.

In this paper, we introduce a compression algorithm using wavelet transform. The principle of wavelet transform is to decompose hierarchically the input image into a series of successively lower resolution reference images and detail images which contain the information needed to be reconstructed back to the next higher resolution level . The histogram of image sub-bands provides us with information

By the nature of images, picture elements in local regions are highly correlated with one another. In such cases, image compression techniques are introduced to reduce the amount of data is needed to represent the same information, either exactly or approximately. In this work DCT/DPCM hybrid approach have been designed and implemented for interlaced images. The image signal was first transformed row-wise using discrete cosine transform (DCT) and a differential pulse code modulation (DPCM) scheme then was used column-wise to get difference signal. For still images the same 3-bit quantizer was employed which makes quantization process easier. For interlaced images 3-bit quantizer was used for the odd field and 2-bit quantizer for even field, since the difference signal of the even field was very small. A compression ratios of about 13:1 was obtained for interlaced image. Objective measurements showed a high peak to peak signal to noise ratio without noticeable impairment.

Stream is a European Telecommunication standard for communication of daralwoice channels in a digital nehvork. This poper will deal with the design and implementation of0 tramparent stream analper, capoble ofhandling (up to 2 Mbps) E l stream and analyzing 30 wice /data channels using an out-oflband Conpzon Channel S i p l i n g System number 7 (CCSS7) protocol. The analper is capable of generating an El sfread and thus can be used for generarion, monitoring and blocking of channels. The Analyzer can perform analysis and maintenance ofEl (Z.048Mbps) lines. As our a d p e r performs the analysisfinctions in the sofiare it is very flexible and can perform many odditional fiatures such as algorifhm and protocols testing and analysis. The workable synchronous Finite Stare Machine (FSM) design ofanalyzer is implemented in Verilog and verified on Altera P FLEXIOK70 FPGA along with its subsequent interfaEing with PC through Enhanced Parallel Port.

In this paper, we introduce a compression algorithm using wavelet transform. The principle of wavelet transform is to decompose hierarchically the input image into a series of successively lower resolution reference images and detail images which contain the information needed to be reconstructed back to the next higher resolution level . The histogram of image sub-bands provides us with information