Adaptive Differential Pulse Code Modulation Research Articles

Gated recurrent unit predictor model-based adaptive differential pulse code modulation speech decoder

Speech coding is a method to reduce the amount of data needs to represent speech signals by exploiting the statistical properties of the speech signal. Recently, in the speech coding process, a neural network prediction model has gained attention as the reconstruction process of a nonlinear and nonstationary speech signal. This study proposes a novel approach to improve speech coding performance by using a gated recurrent unit (GRU)-based adaptive differential pulse code modulation (ADPCM) system. This GRU predictor model is trained using a data set of speech samples from the DARPA TIMIT Acoustic-Phonetic Continuous Speech Corpus actual sample and the ADPCM fixed-predictor output speech sample. Our contribution lies in the development of an algorithm for training the GRU predictive model that can improve its performance in speech coding prediction and a new offline trained predictive model for speech decoder. The results indicate that the proposed system significantly improves the accuracy of speech prediction, demonstrating its potential for speech prediction applications. Overall, this work presents a unique application of the GRU predictive model with ADPCM decoding in speech signal compression, providing a promising approach for future research in this field.

Sequentially Adaptive Differential Pulse Code Modulation Using Adaptive LSP Filters.(Dept.E)

Sequentially Adaptive Differential Pulse Code Modulation Using Adaptive LSP Filters.(Dept.E)

Stream-Based Visually Lossless Data Compression Applying Variable Bit-Length ADPCM Encoding.

Video applications have become one of the major services in the engineering field, which are implemented by server–client systems connected via the Internet, broadcasting services for mobile devices such as smartphones and surveillance cameras for security. Recently, the majority of video encoding mechanisms to reduce the data rate are mainly lossy compression methods such as the MPEG format. However, when we consider special needs for high-speed communication such as display applications and object detection ones with high accuracy from the video stream, we need to address the encoding mechanism without any loss of pixel information, called visually lossless compression. This paper focuses on the Adaptive Differential Pulse Code Modulation (ADPCM) that encodes a data stream into a constant bit length per data element. However, the conventional ADPCM does not have any mechanism to control dynamically the encoding bit length. We propose a novel ADPCM that provides a mechanism with a variable bit-length control, called ADPCM-VBL, for the encoding/decoding mechanism. Furthermore, since we expect that the encoded data from ADPCM maintains low entropy, we expect to reduce the amount of data by applying a lossless data compression. Applying ADPCM-VBL and a lossless data compression, this paper proposes a video transfer system that controls throughput autonomously in the communication data path. Through evaluations focusing on the aspects of the encoding performance and the image quality, we confirm that the proposed mechanisms effectively work on the applications that needs visually lossless compression by encoding video stream in low latency.

Data Transmission at 14.4kb/s OVER 32kb/s ADPCM Channel

Abstract This paper presents new modified QAM modem that operates at data rate of 14.4kb/s to be transmitted over 32kb/s Adaptive Differential Pulse Code Modulation (ADPCM). The purpose of this modified QAM modem is to reduce the nonlinear distortion introduced by ADPCM. The performance of ADPCM is studied considering the standard QAM modem and modified QAM modem with different constellations. The simulation results show that the performance of ADPCM with modified QAM modem is better than its performance with standard QAM modem. Also, the performance with circular constellation is better than rectangular one.

DESIGN AND ANALYSIS OF DIFFERENT TECHNIQUES FOR ANALOG-TO-DIGITAL CONVERSION OF VIBRATION SIGNALS FOR WIRELESS MEASUREMENT SYSTEMS

The aim of this paper is to design, analyze and compare four different systems for ADC (analog-to-digital conversion) of vibration signals. Measurement of vibration signals is of particular importance in many areas, such as predictive maintenance or structural health monitoring. Wireless systems for vibration measurements becomes very topical, due to much easier and cheaper installation compared to wired systems. Due to the lack of transmission bandwidth and energy in wireless measurement systems, the amount of digital data being sent has to be reduced; hence, we have to apply ADC systems that can achieve the required digital signal quality, reducing the bit-rate. Four ADC systems are analyzed, for possible application in wireless measurement systems: PCM (pulse code modulation) based on uniform quantization; DPCM (differential PCM) to exploit high correlation of vibration signals; two adaptive ADC systems to cope with significant variations of characteristics of vibration signals in time - APCM (adaptive PCM) with adaptation on variance and ADPCM (adaptive DPCM), with double adaptation (both on variance and correlation). These ADC models are designed and optimized specifically for vibration signals, based on the analysis of 20 vibration signals from a referent database. An experiment is done, applying designed ADC systems for digitalization of vibration signals. APCM, DPCM and ADPCM systems allow significant bit-rate reduction compared to the PCM system, but with the increasing of complexity, hence the compromise between the bit-rate reduction and complexity is needed.

Detection techniques for mitigating the nonlinear distortion of ADPCM link

This paper presents new detectors developed to handle the severe nonlinear distortion introduced by 32 kb/s Adaptive Differential Pulse Code Modulation (ADPCM). These detectors are tested against previously developed detector named system-B using data transmission at 9.6 kb/s over ADPCM link in cascade with telephone channel. Simulation results show that the error rates of the proposed detectors approach negligible values at certain signal-to-noise-ratio (SNR), while, the error rate of system-B remains constant at certain value.

시그마 델타 변조에 의한 LED 드라이버의 입력 콘트롤러 설계

In this paper, we present the LED dimming control system by using ADPCM (Adaptive Differential Pulse Code Modulation). This ADPCM apparatus accurately controls the LED current with high resolution reducing the RFI (radio frequency interference) due to the spreading out of the harmonics of current of pulses. Additionally, this makes it easier to increase the accuracy of control operation. This study introduces to make a digitally controlled circuit for controlling LED with high-energy efficient by adopting pulse current to LED. The LED current drive system we designed are two systems, the digitally-controlled unit and analog switching mode power supply unit, can be developed separately. The simulation shows the sigma delta modulation of digital to analog converter`s output when the input level is 0.7. From this simulation, the output is approached to accurately 0.15% to target value with 510 pulses.

Effect of Changing the Symbol Rate of QAM Modem on the Performance of 32kb/s ADPCM System

This paper presents three models of Quadrature Amplitude Modulation (QAM) modem operating at data rate of 16.8kb/s to be transmitted over 32kb/s Adaptive Differential Pulse Code Modulation (ADPCM) channel. These modems operate at symbol rates of 2400, 2800, and 3360 baud with associated number of bits per symbol of 7, 6, and 5 respectively. The performance of ADPCM is studied considering these modems with different constellations. The simulation results show that the performance of ADPCM degrades as the symbol rate decreases or number of bits per symbol increases. Also, the performance with circular constellation is better than rectangular one.

An appropriate system for securing real-time voice communication based on ADPCM coding and chaotic maps

This paper presents a very simple and efficient encryption scheme based on controlled chaotic maps and ADPCM (Adaptive Differential Pulse Code Modulation) coding, in order to secure the real-time voice communication for operating at 16, 24, 32 or 40 kbps. This encryption algorithm adopts three main operations one to generate chaotic values using two chaotic logistic maps starting from independent initial conditions, the second to transform them into binary words using random encoding tables and the third to execute some basic operations and substitutions. It has important properties of randomness that can pass NIST batteries of tests. The evaluation and simulation analysis indicate that our proposal possesses an excellent statistical and cryptographic properties; it provides low correlation between adjacent samples in encryption speech, extremely sensitive encryption keys and has a large key space which is sufficient to protect against brute-force attack. As an illustrative example, an application on a commonly-encoder type used in communications, standard ITU-T G.726, is presented.

Performance study of multistage of 40 kb/s ADPCM systems

The contribution of this paper is that the measure of the performance of multistage of 40 kb/s Adaptive Differential Pulse Code Modulation (ADPCM) using signal-to-noise-ratio formula previously derived by AL-Rawi. The multistage performance is tested using QAM signal at data rate of 9.6 kb/s with four types of constellations, rectangular, and (5,11), (4,12), (8,8) circular. The simulation results show that the performance degrades with increasing the number of stages of ADPCM. Also, the performance with circular constellation is better than that with rectangular one.

Modified 24 kb/s ADPCM System

This paper presents new modified 24 kb/s Adaptive Differential Pulse Code Modulation (ADPCM) system. The modified ADPCM uses 4-bit quantizer with sampling rate of 6,000 sample/s, while, the standard ADPCM uses 3-bit quantizer with sampling rate of 8,000 sample/s. The purpose of this modification is to reduce the nonlinear distortion introduced by ADPCM when QAM signal is sent over it. The performances of standard and modified ADPCM are studied using QAM signal at data rate of 9.6 kb/s. The simulation results show that the performance of modified ADPCM is better than standard ADPCM.

Nonlinear backward ADPCM speech coding using kernel methods and online sparsification

ABSTRACTModeling using neural networks and Volterra expansion are widely used in signal processing to account for nonlinear characteristics inherent in natural signals. In spite of their good performance in a wide range of applications, adaptive implementations of these models suffer from severe problems of a large number of parameters, slow convergence, and the risk of being trapped in local minima. Furthermore, inherent instability of the Volterra filters makes them unsuitable for applications that require synthesis or reconstruction, for example, speech coding. Nonetheless, kernel methods in the framework of reproducing kernel Hilbert spaces are emerging solutions that can tackle these problems by extending linear algorithms to spaces created by nonlinear mapping of the input signal. In this paper, we address the problems encountered in nonlinear adaptive coding by employing, for the first time, several kernel adaptive algorithms in the framework of speech coding using the adaptive differential pulse code modulation technique. Particular attention is focused on the effects of various sparsification techniques on the performance of the resultant algorithms. Simulation results show that utilizing kernel methods results in an average improvement of up to 3.4 dB in the signal‐to‐noise ratio of the reconstructed speech. This is while a lower improvement of up to 1.4 dB is achieved by exploiting Volterra filters at the cost of a demanding increase in the complexity, a slight increase in the bit‐rate and introducing a relatively long delay. Copyright © 2012 John Wiley & Sons, Ltd.

A Multiple Description Video Codec With Adaptive Residual Distributed Coding

Multiple description coding (MDC) decomposes one single media into several descriptions and transmits them over different channels for error resilience. Each description contributes to improving the reconstructed media quality when decoded. Distributed video coding (DVC) encodes multiple correlated images and utilizes error correction codes to shift the codec complexity to a joint decoder. Combining MDC with DVC (MDVC) yields a stable codec for mobile encoders. In this paper, to improve the MDVC codec performance, image correlations among the MDVC processing modules were exploited to improve reconstructed video quality and enhance transmission robustness. At the side encoder, a DVC-based adaptive differential pulse code modulation was designed to remove interframe redundancy to enhance rate-distortion performances. For the MDVC central decoding, intradescription and interdescription correlations were utilized to dynamically select the best reconstructed frames from two descriptions, instead of selecting just one description or all key-frames from two descriptions. Experiments showed that, as compared to previous methods, the proposed MDVC control method yielded 1-2 dB higher in image PSNRs for Wyner-Ziv reconstructed frames at the side decoder when encoding low-to-medium complexity videos. For high-complexity videos, it effectively prevents error correction of Wyner-Ziv frames from malfunctioning and yields about 3 dB higher in PSNR. The proposed MDVC central decoder control yields 1-4 dB higher PSNRs, as compared to side decoders. Under lossy transmission, it demonstrates 27-64% smaller PSNR variations, as compared to that of combining key-frames as the decoded video. The proposed MDVC system and control not only improve the DVC reconstructed video quality, but also reduce the quality fluctuation artifacts of MDC coded video for mobile coders.

Adaptive-Compression Based Congestion Control Technique for Wireless Sensor Networks

Congestion in a wireless sensor network causes an increase in the amount of data loss and delays in data transmission. In this paper, we propose a new congestion control technique (ACT, Adaptive Compression-based congestion control Technique) based on an adaptive compression scheme for packet reduction in case of congestion. The compression techniques used in the ACT are Discrete Wavelet Transform (DWT), Adaptive Differential Pulse Code Modulation (ADPCM), and Run-Length Coding (RLC). The ACT first transforms the data from the time domain to the frequency domain, reduces the range of data by using ADPCM, and then reduces the number of packets with the help of RLC before transferring the data to the source node. It introduces the DWT for priority-based congestion control because the DWT classifies the data into four groups with different frequencies. The ACT assigns priorities to these data groups in an inverse proportion to the respective frequencies of the data groups and defines the quantization step size of ADPCM in an inverse proportion to the priorities. RLC generates a smaller number of packets for a data group with a low priority. In the relaying node, the ACT reduces the amount of packets by increasing the quantization step size of ADPCM in case of congestion. Moreover, in order to facilitate the back pressure, the queue is controlled adaptively according to the congestion state. We experimentally demonstrate that the ACT increases the network efficiency and guarantees fairness to sensor nodes, as compared with the existing methods. Moreover, it exhibits a very high ratio of the available data in the sink.

Spherical Logarithmic Quantization

Spherical logarithmic quantization (SLQ) is a vector quantization method for efficiently digitizing analog signals at a high dynamic range and with very low distortion while preserving the original waveform as closely as possible. SLQ is able to operate at a low data rate of, e.g., 2 bits per sample and at a very low signal delay of about ten samples, this corresponds to approximately 200 mus for high-quality audio signals. The technique of SLQ is universally applicable (i.e., not restricted to, e.g., audio signals) and achieves an efficient digital representation of waveforms with high longterm as well as high segmental signal-to-noise ratios. The aim of this paper is to give a detailed description of the SLQ algorithm and to present simulation results on the performance of this new quantization scheme that combines several advantages. After a review of some important basic principles concerning quantization, linear prediction and multidimensional spheres, the SLQ encoder is described. To short vectors of signal samples which are represented in sphere coordinates, logarithmic quantization is applied to the radius and uniform quantization is applied to the angles. This results in the advantage of a constant signal-to-noise ratio over a very high dynamic range at a small loss with respect to the rate-distortion theory. In order to increase the signal-to-noise ratio by exploitation of correlations within the source signal, a solution for the problem of combining this vector quantization scheme with scalar adaptive differential pulse code modulation (ADPCM), i.e., ADPCM with sample by sample backward recursion is presented. Furthermore, an indexing scheme for the quantization cells covering the surface of a multidimensional unit sphere is presented and simulation results using different source signals are given.

Codebook Based Digital Speech Compression

Speech compression has been an area of interest for many researchers, and their objectives remained to reduce the bit rates, also to maintain the speech quality. Adaptive Differential Pulse Code Modulation (ADPCM) was first such scheme that evolved out of PCM and in low bit rate source coding techniques; Code Excited Linear Prediction (CELP) was adopted as standard in the Department of Defense (DoD), USA. In this research a novel approach is developed and compression up to 50% is achieved with negligible loss of quality. This coding technique is developed to use a PCM coded speech, initially, and then substituting 3 to 5 Least Significant Bits (LSB) of every byte at the decoding end from a fixed codebook, randomly.

Bi-Fi: An Embedded Sensor/System Architecture for Remote Biological Monitoring

Wireless-enabled processor modules intended for communicating low-frequency phenomena (i.e., temperature, humidity, and ambient light) have been enabled to acquire and transmit multiple biological signals in real time, which has been achieved by using computationally efficient data acquisition, filtering, and compression algorithms, and interfacing the modules with biological interface hardware. The sensor modules can acquire and transmit raw biological signals at a rate of 32 kb/s, which is near the hardware limit of the modules. Furthermore, onboard signal processing enables one channel, sampled at a rate of 4000 samples/s at 12-bit resolution, to be compressed via adaptive differential-pulse-code modulation (ADPCM) and transmitted in real time. In addition, the sensors can be configured to filter and transmit individual time-referenced "spike" waveforms, or to transmit the spike height and width for alleviating network traffic and increasing battery life. The system is capable of acquiring eight channels of analog signals as well as data via an asynchronous serial connection. A back-end server archives the biological data received via networked gateway sensors, and hosts them to a client application that enables users to browse recorded data. The system also acquires, filters, and transmits oxygen saturation and pulse rate via a commercial-off-the-shelf interface board. The system architecture can be configured for performing real-time nonobtrusive biological monitoring of humans or rodents. This paper demonstrates that low-power, computational, and bandwidth-constrained wireless-enabled platforms can indeed be leveraged for wireless biosignal monitoring.

Packet based echo cancellation for VoIP networks

In today’s modern telephony network, VoIP is fast emerging as one of the main communication techniques. However, the performance and the quality of VoIP are affected by echo. Packet Based Echo Canceller (PBEC) is introduced, as a solution to cancel echo in the VoIP network. PBEC can replace the current echo cancellers, which are located in the Public Switched Telephony Network (PSTN) central switches. The operating principle of the PBEC is explained and its advantages are highlighted. The performance of the PBEC using different speech codecs is also studied. Using the PBEC, a maximum Echo Return Loss Enhancement (ERLE) of 37.39 dB has been achieved when used with the Pulse Code Modulation (PCM) based speech codec. From the simulation results, it can be seen that the performance of the Adaptive Differential Pulse Code Modulation (ADPCM) clearly matches the performance of the PCM based speech codec. The other major problem affecting the VoIP network is the issue of packet loss. This issue of packet loss has been successfully addressed in this paper by the insertion of random values. With the insertion of random values, the ERLE increases by 4.81 dB compared to when there is no insertion of random value. The PBEC with the utilization of random values would make the VoIP a better communication tool.

Signal modification for ADPCM based on analysis-by-synthesis framework

In this letter, we propose a novel approach to improve the performance of the adaptive differential pulse code modulation (ADPCM) codec by modifying the input signal under the analysis-by-synthesis framework. Modification of the input signal is performed such that the ADPCM codec causes less quantization error. When applied to the ITU-T G.726 ADPCM coder, the proposed algorithm improves the output signal-to-noise ratio up to 2.39 dB.

Efficient Compression Method for Cell Animation Video

Animation video is becoming very popular with the availability of low cost computing resources. The cell animation is a popular method, used for producing animation video. In order to efficiently encode these videos, conventional video codecs, such as AutoDesk Animation Pro FLC, Intel Indeo 5, and MPEG-4 can be used to achieve high compression. However, when cell animation videos are compressed at very low bit rate by these traditional codecs, objectionable artifacts, e.g., false color, blurred contours, and blocking artifact, are severely occurred. In this paper, we propose an efficient compression method for cell animation images. The proposed method employs hybrid coding scheme which includes intraframe and interframe coding modes. The intraframe mode consists of color quantization, adaptive differential pulse code modulation, forward classification, and Golomb-Rice coding. The interframe coding consists of block-based techniques and exploits the characteristics of motion. Simulation results show that the proposed method provides superior performance over AutoDesk Animation Pro FLC, MPEG-1, Intel Indeo 5, and MPEG-4 standards.