Application and Development of Wavelet Analysis
Abstract
We have attacked the problem of designing efficient time-frequency computational tools by: (a) Developing selection procedures which shape an analyzing signal from a priori and precomputed front-end computations on input data based on Zak transform and ambiguity function. (b) Implementing and comparing code for computing Gabor coefficients based on methods found in 3, 11. This code uses fast FFT algorithms developed under DARPA contract F49620-89-C- 0020. We have determined that the algorithm based on the deconvolution formula in 4 produces the fastest code and have applied this code using the one-sided exponential window to transient signal detection. (c) Developed a new algorithm for computing classical Gabor coefficients based on the concept of a generalized biorthogonal. This algorithm delays the effects of zero theorem and provides for numerically stable computation of Gabor coefficients locally around known Gabor coefficients. (d) Developed the proper form of finite discrete Gabor transform by periodizing and sampling and presented the results in 10, 32). We have applied these results to Gabor representational schemes for submicron filtering, image reconstruction and image transfer for application to submicron lithography and to designing and constructing optical devices to implement time-frequency representations and to carry out processing on such representations including transient signal detection.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 15, 1992
- Accession Number
- ADA260389
Entities
People
- Richard Tolimieri
Organizations
- City University of New York