Adaptive Delta Modulation System Research Articles

Adaptive Delta Modulation Simulation and Analysis Using MatLab


 
 
 
 The system for converting analog signals to digital signals has become a necessity, considering that the tools currently used are digital computers. One of the analog-to-digital conversion systems is the delta modulation system. In delta modulation, only one bit is used to encode each change in the input signal, where a rising signal is encoded into a one bit and a falling signal is encoded into a zero bit. This can save the bit rate which, when transmitted over the transmission channel, can save the transmission bandwidth, and when stored in computer storage media, can save storage space. However, if the slope of the signal rises and falls sharply, the delta modulation system cannot follow these signal changes, which is called slope overload. To overcome this problem, an adaptive delta modulation system was developed that has variable or adaptive pulse height for both one and zero bits. In this paper, a comparison between the delta modulation system and the adaptive delta modulation system using MatLab application will be simulated and analyzed. From the simulation results, it can be seen that the adaptive delta modulation system is able to overcome slope overload compared to the delta modulation system.
 
 
 

Perbandingan Algoritma Pengkodean Suara Manusia : Adaptive Delta Modulation and Linear Prediction Coding

Coding algorithms human voice with ADM (Adaptive Delta Modulation) and LPC (Linear Prediction Coding) made to the encoding signals digitally produced has bit rate as low as possible, thus saving bandwidth transmission line if it will be distributed to the transmission medium, and save memory or computer storage if it will be stored as data storage. ADM technique different from the LPC, the difference is generally classified on how it is encoded. If the ADM system which is encoded representation of the waveform so often called "waveform coding", while the system is encoded LPC are the parameters of the source of the human voice, so often called the "parametric coding". Human voice coding algorithms to be compared are the results of my own research when conducting studies Bachelor of Engineering and Master of Engineering at ITB. The results of measurements taken from the ADM system materials Bachelor of Engineering Thesis entitled "Low Bit-Rate Delta Modulation", while the LPC system is taken from the material Engineering Master's thesis with the title "Voice Signal Processing with LPC Method". From the measurement results ADM system can generate the bit rate of 16 Kbps, while the LPC system generates the bit rate of 2.4 Kbps with the sound quality is almost the same output quality human voice that can be understood (intelligible speech).

A 2-bit Adaptive Delta Modulation System with Improved Performance

A 2-bit adaptive delta modulation system with improved performance is proposed in this paper. Its main characteristic is a new adaptation algorithm that incorporates both memory and look-ahead instantaneous step-size estimation and leads the modulator into generating a 2-bit output codeword. As shown by computer simulation results, the proposed system offers reduced overshoot and fast response to signal variations in comparison to other similar systems.

Connecting Rural India into the Twenty First Century

Click to increase image sizeClick to decrease image size Additional informationNotes on contributorsM N FaruquiMohammad Naseem Faruqui, former Vice-Chancellor of Aligarh Muslim University, was born on 1 July 1934. He did his BSc from the University of Allahabad and obtained his BTech (Hon), MTech and PhD all from IIT Kharagpur. He served at IIT Kharagpur for 33 years in various capacities including Dean and Deputy Director before joining AMU. He had a distinguished career of Research and Development when he was involved as the Co-ordinator of some major projects of the Ministry of Defence, Department of Electronics (DoE), and Ministry of Human Resources Development. His research contributions were recognised and he was the recipient of the VASVIK award as well as the National Invention Promotion award for his work on Digital Adaptive Delta Modulation system. He has guided a large number of students at Doctoral, Masters and Graduate level. He has published more than thirty research papers in various national and international journals and some of his publications have won awards. He is the joint author of a Textbook named “Basic Electronics”.Currently he is a Professor in the Department of Computer and Communication Systems Engineering, Faculty of Engineering at Universiti Putra Malaysia.

New adaptation algorithm for a two-digit adaptive delta modulation system

A new algorithm for instantaneous step-size adaptation in a two-digit delta modulation system incorporating both memory and look-ahead step estimation is presented. The associated modulator generates output code words which consist of a binary and a ternary digit. Besides the wide range of step changes that it produces in the feedback waveform, it offers reduced overshoots and fast response to signal variations. Performance evaluation made by computer simulation for a band-limited RC-shaped gaussian input signal, simulating speech, reveals a considerable improvement in signal-to-noise ratio when compared with constant factor delta modulation (CFDM) and linear delta modulation (LDM) systems operating at the same output bit rate.

A single-chip adaptive delta modulator with optimum performance

This paper describes the design of a high performance Si-Gate CMOS LSI circuit for an Adaptive Delta Modulation System (ADM). The circuit design is based on 4 μ design rules. The size of the die is approximately 25 mm 2 and the circuit operates synchronously under the control of an 8 MHz two phase non-overlapping clock. A fault tolerant scheme is used at the comparator section for reliability improvement purposes. The adaptation logic of the system is based on the algorithm introduced in [2] where a rigorous proof is provided for showing the optimality of the algorithm in terms of performance. This paper demonstrates the feasibility of implementing this algorithm with a single chip adaptive delta modulator.

A Study of Random Channel Errors for an ADM System

This paper constitutes a mathematical analysis of the effects of random channel errors when the transmitted signal is in adaptive delta modulation (ADM) format. This study not only permits us to model the behavior of an ADM signal, with respect to errors, but also provides a method for controlling excessive signal distortion, particularly for high bit error rates. Our analysis shows that the decoded error signal exhibits both a dc and an ac component. The dc error is controlled with a leaky accumulator and an appropriate output filter. The ac error is shown to be proportional to the original signal and we are able to control its amplitude by artificial error injection. This yields an effective way of improving performance in a noisy environment. We present computer simulation results to verify our analysis and error control with a variety of test signals.

Analysis and design of a broadband delta modulation system

A simple treatment is provided of the analysis of an adaptive delta modulation system for evaluating the performance of the system in terms of complexity, signalto- noise ratio and dynamic range. The analysis assumes a simple adaptation algorithm and a normal density function input signal with flat spectrum.A brief description of the implementation of the system is given and finally the experimental results are compared with the theoretical results.

A Nonuniform Sampling Approach to Data Compression

A nonuniform sampling approach to digital encoding of analog sources is proposed. The nonuniform sampler is basically a level crossing detector (LCD) which produces a sample whenever the input to the LCD crosses a threshold level. The information about the source signal is contained in the time intervals between level crossings and in the directions of level crossings. By assigning strings of the 2-tuple 00 to represent the time between level crossings and 01 and 10 to denote the directions of level crossings, the output binary sequence of the nonuniform sampling encoder (NSE) contains a high probability of the 0 symbol, which makes it suitable for further simple run-length encoding (RLE) to attain a good overall compression ratio. Introduction of prediction converts the NSE to a nonuniform sampling predictive coding (NSPC) scheme, which, depending on the source, can potentially improve the compression ratio. Results obtained in the encoding of a band-limied Gaussian source and a rasterscanned black and white still image reveal that an NSE/RLE or NSPC/ RLE system exhibits performance superior to that of an adaptive delta modulation system.

Quantization Noise in Adaptive Delta Modulation Systems

New analytical formulas for quantization noise of two widely known adaptive delta modulation (ADM) systems, continuously variable slope delta modulation (CVSD) and Jayant's firstorder constant factor delta modulation (CFDM), have been obtained. These formulas are derived based upon the previously obtained results for linear delta modulation (LDM) and adaptive differential pulse code modulation (ADPCM). To verify the results, computer simulation has been done using band-limited Gaussian signals. Close agreements between the formulas and the simulation results have been obtained in the wide range of the input signal level.

A Study of the Comparative Performance of Adaptive Delta Modulation Systems

A performance comparison of three representative ADM systems has been made by computer simulation using real speech. The three systems studied are continuously variable slope delta modulation (CVSD), Jayant's constant factor delta modulation (CFDM), and a modified version of Un and Magill's hybrid companding delta modulation (HCDM). Among the three systems, HCDM yields the best performance in signal-to-quantization noise ratio (SQNR) and dynamic range regardless of the channel bit error rate. Comparing CVSD and CFDM in an ideal channel, the dynamic range of the latter is significantly wider than that of the former, although their peak SQNR's are almost the same. In a noisy channel, CFDM degrades more rapidly than the other two as the bit error rate increases. In the channel with an error rate above 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> , the use of CFDM appears to be impractical when the bit rate is below 16 khits/s. However, intelligible speech transmission is possible with HCDM or CVSD even at the error rate of as high as 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> .

A digitally adaptive delta modulation system

An adaptive delta modulation system using digital control circuitry and an exponential strategy is described. The design and circuit details of an experimental system for the audio (speech) frequency range are presented with an account of the computer simulation of the system as designed.

Estimation of the Signal-to-Noise Ratio in High Information and Constant Factor Delta Modulation Systems

A "statistical average step size," γ <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">av</inf> , which is a function of the rms power of a band-limited white Gaussian input signal, is defined for high information and first order constant factor delta modulation systems. The signal-to-noise ratios (SNR) are then calculated for these instantaneously adaptive delta modulation systems by substituting γ <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">av</inf> for the fixed step size in the formulas for quantization (i.e., granular) and slope-overload noise applicable to linear (single integration) delta modulation systems. The calculated SNRs are in close agreement to those obtained by computer simulations. As γ <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">av</inf> is difficult to calculate exactly, an empirical expression is found which is applicable to different encoding conditions. This empirically formulated γ <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">av</inf> can be used to estimate SNR to an acceptable accuracy for most practical situations. A noise component not present in linear delta modulation is identified and called "overshoot noise" and the cross-correlation ρ <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">xe</inf> between input and error signals is studied. The SNR and ρ <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">xe</inf> for linear delta modulation are presented as reference bases.

Two-loop ternary adaptive delta modulation

A 2-loop ternary adaptive delta-modulation system is described which produces a peak s.n.r. of 20.5 dB, and for an s.n.r. of 15 dB, its dyamic range is 22dB when the input signal is RC shaped noise band limited to 2.5 kHz and the sampling rate is 8 kHz.

Stability of Adaptive Delta Modulation systems with memory

It is well known that multiplicative Adaptive Delta Modulation (ADM) systems with a 1-bit memory are unstable if the adaptation parameters P and Q are such that PQ &amp;gt; 1 [Jayant, “Adaptive Delta Modulation with a 1-Bit Memory,” BSTJ 48 (Feb. 1969)]. Furthermore, for this class of ADM systems it has been generally accepted that the maximum signal-to-noise ratio (SNR) occurs at PQ = 1 and P = 1.5. Subsequently, Zetterberg et al. have shown (1) that such systems can be made to perform stably with PQ &amp;gt; 1, and (ii) that the point at which maximum SNR occurs is dependent upon the class of the input signal [Zetterberg and Uddenfelt, “Adaptive Delta Modulation with Delayed Decision,” IEEE Trans. Comm. COM-22 (Sept. 1974)]. Effectively, Zetterberg uses a limited step size to stabilize the ADM system with a 1-bit memory and PQ &amp;gt; 1. In this paper it is demonstrated that this form of ADM implementation can lead to the loss of low-energy signals, rendering the technique impractical for speech encoding. Alternative techniques are proposed for implementing ADM systems which are stable across a wide range of values for PQ and P. For speech, the maximum SNR is observed for values of P &amp;gt; 2.

Linear and adaptive delta modulation

New results are presented, offering insight into the performance and optimization of linear and adaptive delta modulation, together with a comparison with pulse code modulation. The results are applied to three cases of practical interest: television, speech, and broadband signals. The results are presented as follows: first, a characterization of the quantization noise of linear delta modulation (DM) is given; second, an adaptive DM system which seems promising for television and speech is evaluated; and third, a comparison between pulse code modulation (PCM) and adaptive DM is made for speech, television, and broadband signals. It is concluded that 1) the adaptive system provides DM with a companding capability, 2) adaptive DM offers a bit rate or channel bandwidth reduction capability in comparison with PCM for television signals, 3) adaptive DM appears better suited to television and speech signals than linear DM, 4) the maximum S/N performance of adaptive DM is the same as that of linear DM, 5) the companding improvement offered by adaptive DM is not limited by the same practical considerations as those of PCM, and 6) the S/N performance of adaptive DM is the same for both Gaussian and exponential signal densities.