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An Architectural Framework for VLSI Time-Recursive Computation with Applications
(1993)
The time-recursive computation model has been proven as a particularly useful tool in audio, video, radar and sonar real- time data processing architectures. Unlike the FFT based architectures, the time-recursive ones ...
Minimum Mean Square Error Estimation of Connectivity in Biological Neural Networks
(1991)
A minimum mean square error (MMSE) estimation scheme is employed to identify the synaptic connectivity in neural networks. This new approach can substantially reduce the amount of data and the computational cost involved ...
Adaptive Array Systems Using QR-Based RLS and CRLS Techniques with Systolic Array Architectures
(1991)
In this dissertation the basic techniques for designing more sophisticated adaptive array systems are first developed. Then several systolic architectures based on numerically stable and computationally efficient algorithms ...
Dual-State Systolic Architectures for Adaptive Filtering Using Up/Downdating RLS
(1991)
We propose a dual-state systolic structure to perform joint up/down-dating operations encountered in windowed recursive least squares (RLS) estimation problems. It is derived by successively performing Givens rotations for ...
An ESPRIT Algorithm for Tracking Time-Varying Signals
(1992)
ESPRIT is a successful algorithm for determining the constant directions of arrival of a set of narrowband signals on an array of sensors. Unfortunately, its computational burden makes it unsuitable for real time processing ...
Unified Parallel Lattice Structures for Time-Recursive Discrete Cosine/Sine/Hartley Transforms
(1991)
The problems of unified efficient computations of the discrete cosine transform (DCT), discrete sine transform (DST), discrete Hartley transform (DHT), and their inverse transforms are considered. In particular, a new ...
Multi-phase Systolic Algorithms for Spectral Decomposition
(1991)
In this paper, we propose two multi-phase systolic algorithms to solve the spectral decomposition problem based on the QR algorithm. The spectral decomposition is one of the most computationally intensive modern signal ...
Fast Orthogonalization Algorithm and Parallel Implementation for AR Spectral Estimation Based on Forward-Backward Linear Prediction
(1991)
High-resolution spectral estimation is an important subject in many applications of modern signal processing. The fundamental problem in applying various high-resolution spectral estimation algorithms is the computational ...
Mathematical Programming Algorithms for Regression-based Nonlinear Filtering in IRN
(1997)
Constrained regression problems appear in the context of optimal nonlinear filtering, as well as in a variety of other contexts, e.g., chromatographic analysis in chemometrics and manufacturing, and spectral estimation. ...
VLSI Algorithms and Architectures for Time-Recursive Discrete Sinuoidal Transforms with Applications to Real-Time Video Communications
(1992)
In this dissertation, we address the problem of developing efficient VLSI algorithms and architectures for discrete sinusoidal transforms in real-time applications for video communication systems. The major difficulty of ...