Signal Processing Commons^™

Signal Approximation With A Wavelet Neural Network, Charles M. Westphal

Theses and Dissertations

This study investigated the use of Wavelet Neural Networks (WNN) for signal approximation. The particular wavelet function used in this analysis consisted of a summation of sigmoidal functions (a sigmoidal wavelet). The sigmoidal wavelet has the advantage of being easily implemented in hardware via specialized electronic devices like the Intel Electronically Trainable Analog Neural Network (ETANN) chip. The WNN representation allows the determination of the number of hidden-layer nodes required to achieve a desired level of approximation accuracy. Results show that a bandlimited signal can be accurately approximated with a WNN trained with irregularly sampled data. Signal approximation, Wavelet neural …

Signal Processing Methodologies For An Acoustic Fetal Heart Rate Monitor, Robert A. Pretlow Iii

Electrical & Computer Engineering Theses & Dissertations

Research and development is presented of real time signal processing methodologies for the detection of fetal heart tones within a noise-contaminated signal from a passive acoustic sensor. A linear predictor algorithm is utilized for detection of the heart tone event and additional processing derives heart rate. The linear predictor is adaptively "trained" in a least mean square error sense on generic fetal heart tones recorded from patients. A real time monitor system is described which outputs to a strip chart recorder for plotting the time history of the fetal heart rate. The system is validated in the context of the …

A Frequency Domain Digital Signal Processor For Laser Velocimeter Systems, Andreas Evangelos Savvakis

Electrical & Computer Engineering Theses & Dissertations

A new signal processor for laser velocimeter systems is proposed. The proposed processor incorporates automatic initialization, real time operation, and can efficiently process input signals comprised of as low as 150 photons, with mean oscillation frequency up to 100 MHZ, and input turbulence from 0 to 20%. A bank of digital bandpass filters is employed for the energy spectrum estimation of the input signal. A deterministic model is developed to describe the relationship between the filter output energies and the input signal parameters. The input frequency is estimated by linearly weighting the filter output energies. A spline function approximation approach …

Design Of Efficient Algorithms Through Minimization Of Data Transfers, Yong Mo Chong

Electrical & Computer Engineering Theses & Dissertations

This thesis explores the time optimal implementation of computational graphs on a finite register machine. The implementation fully exploits the machine architecture, especially, the number of registers. The derived algorithms allow one to obtain time efficient implementations of a given graph in machines with a known number of registers.

These optimization procedures are applied to digital signal processing graphs. It is shown that the regular structure of these graphs allows one to identify computational kernels which, when used repeatedly, can cover the entire graph. The l- and r-register implementations of Hadamard and Fast Fourier Transforms using various computational kernels are …