Adaptive identification by systolic arrays. Master's thesis
This thesis is concerned with the implementation of an adaptive-identification algorithm using parallel processing and systolic arrays. In particular, discrete samples of input and output data of a system with uncertain characteristics are used to determine the parameters of its model. The identification algorithm is based on recursive least squares, QR decomposition, and block-processing techniques with covariance resetting. Along similar lines as previous approaches, the identification process is based on the use of Givens rotations. This approach uses the Cordic algorithm for improved numerical efficiency in performing the rotations. Additionally, floating-point and fixed-point arithmetic implementations are compared.
- Research Organization:
- Naval Postgraduate School, Monterey, CA (USA)
- OSTI ID:
- 7123045
- Report Number(s):
- AD-A-193532/9/XAB
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
990210* -- Supercomputers-- (1987-1989)
ALGORITHMS
CHEMICAL REACTIONS
COMPUTER ARCHITECTURE
COMPUTER NETWORKS
DECOMPOSITION
EFFICIENCY
ELECTRONIC CIRCUITS
EQUATIONS
INTEGRATED CIRCUITS
MATHEMATICAL LOGIC
MATHEMATICS
MICROELECTRONIC CIRCUITS
NUMERICAL ANALYSIS
PARALLEL PROCESSING
PROGRAMMING
SAMPLING