Design of reverse converters for the multi-moduli residue number systems with moduli of forms 2a, 2b - 1, 2c + 1

Residue number system (RNS) is a non-weighted integer number representation system that is capable of supporting parallel, carry-free and high speed arithmetic. This system is error-resilient and facilitates error detection, error correction and fault tolerance in digital systems. It finds applications in Digital Signal Processing (DSP) intensive computations like digital filtering, convolution, correlation, Discrete Fourier Transform, Fast Fourier Transform, etc. The basis for an RNS system is a moduli set consisting of relatively prime integers. Proper selection of this moduli set plays a significant role in RNS design because the speed of internal RNS arithmetic circuits as well as the speed and complexity of the residue to binary converter (R/B or Reverse Converter) have a large dependency on the form and number of the selected moduli. Moduli of forms 2a, 2b- 1, 2c + 1 (a, b and c are natural numbers) have the most use in RNS moduli sets as these moduli can be efficiently implemented using usual binary hardware that lead to simple design. Another important consideration for the reverse converter design is the selection of an appropriate conversion algorithm from Chinese Remainder Theorem (CRT), Mixed Radix Conversion (MRC) and the new Chinese Remainder Theorems (New CRT I and New CRT II). This research is focused on designing reverse converters for the multi-moduli RNS sets especially four and five moduli sets with moduli of forms 2a, 2b- 1, 2c + 1 . The residue to binary converters are designed by applying the above conversion algorithms in different possible ways and facilitating the use of modulo (2k) and modulo (2k – 1) adders that lead to simple design of adder based architectures and VLSI efficient implementations (k is a natural number). The area and delay of the proposed converters is analyzed and an efficient reverse converter is suggested from each of the various four and five moduli set converters for a given dynamic range

Design and implementation of high-radix arithmetic systems based on the SDNR/RNS data representation

This project involved the design and implementation of high-radix arithmetic systems based on the hybrid SDNRIRNS data representation. Some real-time applications require a real-time arithmetic system. An SDNR/RNS arithmetic system provides parallel, real-time processing. The advantages and disadvantages of high-radix SDNR/RNS arithmetic, and the feasibility of implementing SDNR/RNS arithmetic systems in CMOS VLSI technology, were investigated in this project. A common methodological model, which included the stages of analysis, design, implementation, testing, and simulation, was followed. The combination of the SDNR and RNS transforms potential complex logic networks into simpler logic blocks. It was found that when constructing a SDNRIRNS adder, factors such as the radix, digit set, and moduli must be taken into account. There are many avenues still to explore. For example, implementing other arithmetic systems in the same CMOS VLSI technology used in this project and comparing them to equivalent SDNR/RNS systems would provide a set of benchmarks. These benchmarks would be useful in addressing issues relating to relative performance

An electronically focused multiple beam side scan sonar

Phased arrays have been in use since World War II but their commercial application has been constrained by the bulk and cost of the beam forming system. High resolution side scan sonar systems have many operational parameters that may only be extended with the aid of phased arrays, the resolution and the imaging rate being the most important. This thesis describes a microprocessor controlled dynamically focused side scan sonar where high resolution and high image acquisition rates are achieved. Dynamic focusing prevents the depth of field limitations of fixed focus arrays by updating the array phases at regular intervals so as to create a focal point which recedes from the array in synchronism with the returning echoes from the transmitted pulse. A high image acquisition rate is achieved through the simultaneous formation of multiple beams. Using a microprocessor as a low-cost controller demands rapidly executable software and a little specialized hardware. Programmable quadrature phase shifters give phase and amplitude control. A beam forming board combines the phase shifted signals into a beam and samples it. A 'time domain multiplexed' transmitter solves the problem of efficient insonification of swaths. The system timing is complex; while image samples are captured data is formatted and presented for recording on a chart recorder. This occurs in real-time, while the focus of each of the multiple beams is changed almost every two meters. Tank tests of the completed system provide confirmation of the resolution predicted with theory and computer simulation. Sea trials confirm that resolution close to that predicted may be obtained under operational circumstances. The results obtained fully justify the assertion that low cost microprocessor controlled dynamically focused multiple beam phased arrays are both an attainable and an attractive solution to the problems faced by the designer of high resolution side scan sonar systems

Modeling and Analysis of Power Processing Systems

The feasibility of formulating a methodology for the modeling and analysis of aerospace electrical power processing systems is investigated. It is shown that a digital computer may be used in an interactive mode for the design, modeling, analysis, and comparison of power processing systems

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

Low-power current-mode ADC for CMOS sensor IC

A low-energy current-mode algorithmic pipelined ADC targeted for use in distributed sensor networks is presented. The individual nodes combine sensing, computation and communications into an extremely small volume. The nodes operate with very low duty cycle due to limited energy. Ideally these sensor networks will be massive in size and dense in order to promote redundancy. In addition the networks will be collectively intelligent and adaptive. To achieve these goals, distributed sensor networks will require very small,inexpensive nodes that run for long periods of time on very little energy. One component of such network nodes is an A/D converter. An ADC acts as a crucial interface between the sensed environment and the sensor network as a whole. The work presented here focuses on moderate resolution, and moderate speed, but ultra-low-power ADCs. The 6 bit current-mode algorithmic pipelined ADC reported here consumes 8 pJ/bit samples at 0.65V supply and 130 kS/s. The current was chosen as the information carrying quantity instead of voltage as it is more favorable for low-voltage and low-power applications. The reference current chosen was 150nA. All the blocks are using transistors operating in subthreshold or weak inversion region of operation, to work in low-voltage and low current supply. The DNL and INL plots are given in simulation results section. The area of the overall ADC was 0.046 mm2 only

Analysis of electric propulsion electrical power conditioning component technology. Volume 1 - Data bank Final report

Analysis of electric propulsion electric power conditioning component technology - data revie