Thesis (Ph. D.)--University of Hong Kong, 2005.

Thesis (Ph.D.) OGI School of Science & Engineering at OHSU, October 2007. / Includes bibliographical references (leaves 149-152).

This thesis investigates an implementation of speech recognition front-end. It is an application specific integrated circuit (ASIC) solution. A Mel Cepstrum algorithm is implemented for the feature extraction. We present a new mixed split-radix and radix-2 Fast Fourier Transform (FFT) algorithm, which can effectively minimize the number of complex multiplications in the speech recognition front-end. A prime length discrete cosine transform (DCT) is done effectively through the use of two shorter length correlations. The algorithm results in a circular correlation structure that is suitable for a constant coefficient multiplication and shift-register realization. The multiplicative normalization algorithm is used for square root function. Radix-2 algorithm is used in the first 5 stages and radix-4 algorithm is used in the other stages to speed up the convergence. A similar normalization algorithm is present for natural logarithm. / Graduation date: 2002

Thesis (Ph. D.)--University of Texas at Austin, 1999. / Vita. Includes bibliographical references (leaves 116-121). Available also in a digital version from Dissertation Abstracts.

published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

No description available.

Techn. Univ., Diss.--Lungby, 1994.

Thesis (M. S.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Laskar, Joy; Committee Member: Anderson, David; Committee Member: Cressler, John. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Thesis (Ph. D.)--University of Washington, 1999. / Vita. Includes bibliographical references (leaves 126-140).

Finding errors in applications has been achieved using a wide variety of techniques. Some tools instrument the application to check for program properties dynamically whereas others analyze the program statically. We use a technique that analyzes a program's execution by binary runtime instrumentation. Unlike tools that work on a particular language or an intermediate representation of a language, our approach works directly on binaries and hence it is not bound to any language. In order to instrument binaries, we use a binary instrumentation system called Pin, which provides APIs to instrument the application at runtime. We have built an infrastructure using Pin called Top that allows program entities like variables and events to be traced. Using finite automata we can check if certain events take place during the execution of the program. Top consists of a Tracing System that can trace movement of pointers to memory locations or 32-bit data values and keeps track of all their copies. It also provides an Event Framework that reports the occurrence of events such as function calls or returns. Top provides a programming interface which allows querying for particular events. The query is compiled with Top to produce a customized analysis tool, also called client. Running the analysis tool with the application, under Pin, results in events of interest being detected and reported. Using Top, we built a Memory Checker that checks for incorrect usage of dynamic memory allocation APIs and semantically incorrect accesses to dynamically allocated memory. Since we perform fine-grained checking by tracing references, our memory checker found some errors that a popular memory checker called valgrind did not. We have also built an MPI Checker which is used to check if programs use MPI's asynchronous communication primitives properly. This checker can detect errors related to illegal data buffer accesses and errors where the programmer inadvertently overwrote a handle needed to finish the processing of a request. / Master of Science