Design and Implementation of an RNS-based 2D DWT Processor

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Mathematics and Digital Signal Processing

Modern computer technology has opened up new opportunities for the development of digital signal processing methods. The applications of digital signal processing have expanded significantly and today include audio and speech processing, sonar, radar, and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others. This Special Issue is aimed at wide coverage of the problems of digital signal processing, from mathematical modeling to the implementation of problem-oriented systems. The basis of digital signal processing is digital filtering. Wavelet analysis implements multiscale signal processing and is used to solve applied problems of de-noising and compression. Processing of visual information, including image and video processing and pattern recognition, is actively used in robotic systems and industrial processes control today. Improving digital signal processing circuits and developing new signal processing systems can improve the technical characteristics of many digital devices. The development of new methods of artificial intelligence, including artificial neural networks and brain-computer interfaces, opens up new prospects for the creation of smart technology. This Special Issue contains the latest technological developments in mathematics and digital signal processing. The stated results are of interest to researchers in the field of applied mathematics and developers of modern digital signal processing systems

A computer-aided design for digital filter implementation

Imperial Users onl

Algorithms and VLSI architectures for parametric additive synthesis

A parametric additive synthesis approach to sound synthesis is advantageous as it can model sounds in a large scale manner, unlike the classical sinusoidal additive based synthesis paradigms. It is known that a large body of naturally occurring sounds are resonant in character and thus fit the concept well. This thesis is concerned with the computational optimisation of a super class of form ant synthesis which extends the sinusoidal parameters with a spread parameter known as band width. Here a modified formant algorithm is introduced which can be traced back to work done at IRCAM, Paris. When impulse driven, a filter based approach to modelling a formant limits the computational work-load. It is assumed that the filter's coefficients are fixed at initialisation, thus avoiding interpolation which can cause the filter to become chaotic. A filter which is more complex than a second order section is required. Temporal resolution of an impulse generator is achieved by using a two stage polyphase decimator which drives many filterbanks. Each filterbank describes one formant and is composed of sub-elements which allow variation of the formant’s parameters. A resource manager is discussed to overcome the possibility of all sub- banks operating in unison. All filterbanks for one voice are connected in series to the impulse generator and their outputs are summed and scaled accordingly. An explorative study of number systems for DSP algorithms and their architectures is investigated. I invented a new theoretical mechanism for multi-level logic based DSP. Its aims are to reduce the number of transistors and to increase their functionality. A review of synthesis algorithms and VLSI architectures are discussed in a case study between a filter based bit-serial and a CORDIC based sinusoidal generator. They are both of similar size, but the latter is always guaranteed to be stable

The Fifth NASA Symposium on VLSI Design

The fifth annual NASA Symposium on VLSI Design had 13 sessions including Radiation Effects, Architectures, Mixed Signal, Design Techniques, Fault Testing, Synthesis, Signal Processing, and other Featured Presentations. The symposium provides insights into developments in VLSI and digital systems which can be used to increase data systems performance. The presentations share insights into next generation advances that will serve as a basis for future VLSI design

Transmitter based techniques for ISI and MAI mitigation in CDMA-TDD downlink

The third-generation (3G) of mobile communications systems aim to provide enhanced voice, text and data services to the user. These demands give rise to the complexity and power consumption of the user equipment (UE) while the objective is smaller, lighter and power efficient mobiles. This thesis aims to examine ways of reducing the UE receiver’s computational cost while maintaining a good performance. One prominent multiple access scheme selected for 3G is code division multiple access. Receiver based multiuser detection techniques that utilise the knowledge of the downlink channel by the mobile have been extensively studied in the literature, in order to deal with multiple access and intersymbol interference. However, these techniques result in high mobile receiver complexity. Recently, work has been done on algorithms that transfer the complexity from the UE to the base station by exploiting the fact that in time division duplex mode the downlink channel can be known to the transmitter. By linear precoding of the transmitted signal the user equipment can be simplified to a filter matched to the user’s spreading code. In this thesis the problem of generic linear precoding is analysed theoretically and a method for analytical calculation of BER is developed. The most representative of the developed precoding techniques are described under a common framework, compared and classified as bitwise or blockwise. Bitwise demonstrate particular advantages in terms of complexity and implementation but lack in performance. Two novel bitwise algorithms are presented and analysed. They outperform significantly the existing ones, while maintain a reduced computational cost and realisation simplicity. The first, named inverse filters, is the Wiener solution of the problem after applying a minimum mean squared error criterion with power constraints. The second recruits multichannel adaptive algorithms to achieve the same goal. The base station emulates the actual system in a cell to converge iteratively to the pre-filters that precode the transmitted signals before transmission. The advantages and the performance of the proposed techniques, along with a variety of characteristics are demonstrated by means of Monte Carlo simulations