Sampled data systems and generating functions

Application of Z-transforms to sampled-data system

Generalization of a 3-D resonator model for the simulation of spherical enclosures

A rectangular enclosure has such an even distribution of resonances that it can be accurately and efficiently modelled using a feedback delay network. Conversely, a non rectangular shape such as a sphere has a distribution of resonances that challenges the construction of an efficient model. This work proposes an extension of the already known feedback delay network structure to model the resonant properties of a sphere. A specific frequency distribution of resonances can be approximated, up to a certain frequency, by inserting an allpass filter of moderate order after each delay line of a feedback delay network. The structure used for rectangular boxes is therefore augmented with a set of allpass filters allowing parametric control over the enclosure size and the boundary properties. This work was motivated by informal listening tests which have shown that it is possible to identify a basic shape just from the distribution of its audible resonances.Comment: 39 pages, 16 figures, 6 tables. Accepted for publication in Applied Signal Processin

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

Implementing IIR filters via residue number systems.

by Tai Leong Charn.Bibliography: leaves R-i-iiiThesis (M.Phil.)--Chinese University of Hong Kong, 198

Acoustic modeling using the digital waveguide mesh

The digital waveguide mesh has been an active area of music acoustics research for over ten years. Although founded in 1-D digital waveguide modeling, the principles on which it is based are not new to researchers grounded in numerical simulation, FDTD methods, electromagnetic simulation, etc. This article has attempted to provide a considerable review of how the DWM has been applied to acoustic modeling and sound synthesis problems, including new 2-D object synthesis and an overview of recent research activities in articulatory vocal tract modeling, RIR synthesis, and reverberation simulation. The extensive, although not by any means exhaustive, list of references indicates that though the DWM may have parallels in other disciplines, it still offers something new in the field of acoustic simulation and sound synth

Utilizing digital design techniques and circuits to improve energy and design efficiency of analog and mixed-signal circuits

Technology scaling has long driven large growth in the electronics market. With each successive technology generation, digital circuits become more power and area efficient. The large performance increases realized for digital circuits due to digital scaling have not translated to similar performance improvements for analog circuits. First, noise-limited analog circuits are not capable of leveraging the reduced parasitics of advanced processes, since capacitor sizes are generally set by noise requirements. Second, analog circuit performance is closely tied to the achievable device intrinsic gain, which degrades as process sizes shrink. Reduced supply voltages further exacerbate this issue, as the achievable gain per stage is limited by the number of devices that can be stacked while maintaining all devices in saturation. Finally, process variation increases with decreased feature sizes, so analog circuits have deal with increased mismatch and wider variations in threshold voltages, increasing the time required to design a circuit that is robust across process, voltage, and temperature (PVT) variation. This work seeks to address the limitations of analog circuits in advanced technologies by leveraging digital techniques and digital-like circuits that offer improved scalability. The first half of this dissertation investigates replacing the traditional closed-loop residue amplifier in a pipeline analog-to-digital converter (ADC) with an open loop dynamic amplifier. Previous works incorporating dynamic amplifiers have struggled to achieve large gains and have suffered from offset mismatch between the comparator and amplifier, which will only get worse in more advanced technologies. We propose the usage of a residue amplifier that combines an integration stage, to ensure low noise operation, with a positive feedback stage, to ensure high gain and high speed operation. By utilizing this topology, the proposed amplifier was the first dynamic amplifier to achieve a high gain of 32. Additionally, the proposed amplifier can reuse existing comparator hardware in the ADC, removing all offset mismatch between comparator and amplifier. Digital calibration techniques were applied to ensure a constant gain across PVT. The next part of this dissertation tries to overcome the scaling challenges for noise-limited ADCs with band-limited input signals. By leveraging digital filtering techniques to generate a prediction of the band-limited signal, the conversion can be limited to a range that is a fraction of the total ADC input range, allowing for significant decreases in reference and comparator power consumption. This work extends previous works by enabling accurate predictions for any band-limited signal characteristic. Previous works only focused on accurate predictions for low-activity signals. Finally, the large compute power enabled by modern technology scaling is leveraged to improve the design efficiency of analog circuits. A new automated circuit sizing tool is proposed that can achieve better performance than manual designs done by experts in a much shorter amount of time. All of these techniques help to alleviate the power and design efficiency limitations caused by technology scaling.Electrical and Computer Engineerin

Noise-Shaping SAR ADCs.

This work investigates hybrid analog-to-digital converters (ADCs) that combine the phenomenal energy efficiency of successive-approximation (SAR) ADCs with the resolution enhancement strategies used by noise-shaping converters. Because charge-redistribution SAR ADCs contain few active components and rely on highly digital controllers, SAR ADCs demonstrate the best energy efficiencies of all low bandwidth, moderate resolution converters (~10 bits). SAR ADCs achieve remarkable power efficiency at low resolution, but as the resolution of the SAR ADC increases, the specifications for input-referred comparator noise become more stringent and total DAC capacitance becomes too large, which degrades both power efficiency and bandwidth. For these reasons, lower resolution, lower bandwidth applications tend to favor traditional SAR ADC architectures, while higher bandwidth, higher resolution applications tend to favor pipeline-SARs. Although the use of amplifiers in pipeline-assisted SARs relaxes the comparator noise requirements and improves bandwidth, amplifier design becomes more of a challenge in highly scaled processes with reduced supply voltages. In this work, we explore the use of feedback and noise-shaping to enhance the resolution of SAR ADCs. Unlike pipeline-SARs, which require high-gain, linear amplifiers, noise-shaping SARs can be constructed using passive FIR filter structures. Furthermore, the use of feedback and noise-shaping reduces the impact of thermal kT/C noise and comparator noise. This work details and explores a new class of noise-shaping SARs.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/113647/1/fredenbu_1.pd