Kalman filtering in noisy nonlinear systems using a jump matrix approach
<p>A computationally efficient estimation technique is presented for a class of nonlinear systems consisting of memoryless nonlinearities combined with linear dynamic processes. The modeling approach is based on a useful sampled-data method for simulating such systems by adding a system state...
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Format: | Others |
Language: | en |
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Virginia Tech
2014
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Online Access: | http://hdl.handle.net/10919/43172 http://scholar.lib.vt.edu/theses/available/etd-06112009-063610/ |