Title :
Statistical wavelet and filter bank optimization
Author :
Djokovic, Igor ; Vaidyanathan, P.P.
Author_Institution :
Dept. of Electr. Eng., California Inst. of Technol., Pasadena, CA, USA
Abstract :
We deal with three problems of optimal multiresolution representation and approximation of random processes. The first problem is that of finding a scaling function which will give the best approximation of a random process at a given scale. Approximation of inner products of ensemble members of a random process and a scaling function is the second problem. The approach to the above problems is similar. We first find the autocorrelation functions of errors, then their power spectra and finally, the variances. The third problem is the coding gain optimization of a subband coding system, more specifically, the choice of filters in a filter bank which maximizes the coding gain. An optimization algorithm is derived and an efficient implementation scheme proposed
Keywords :
analogue-digital conversion; digital filters; encoding; filtering and prediction theory; optimisation; random processes; signal processing; statistical analysis; wavelet transforms; FIR filter banks; autocorrelation functions; coding gain optimization; errors; filter bank optimization; inner products; optimal multiresolution representation; optimization algorithm; power spectra; random processes approximation; scaling function; signal analysis; statistical wavelet optimisation; subband coding system; variances; Autocorrelation; Design optimization; Filter bank; Finite impulse response filter; Multiresolution analysis; Phase change materials; Random processes; Signal design; Signal resolution; Virtual manufacturing;
Conference_Titel :
Signals, Systems and Computers, 1993. 1993 Conference Record of The Twenty-Seventh Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-4120-7
DOI :
10.1109/ACSSC.1993.342437