Title :
A mutual information measure for feature selection with application to pulse classification
Author :
Barrows, Geoffrey L. ; Sciortino, John C., Jr.
Author_Institution :
Tectical Electron. Warfare Div., Naval Res. Lab., Washington, DC, USA
Abstract :
This paper presents a method of constructing a low dimensional representation of a pulse signal that preserves the information necessary to classify the pulse. A large set of “atomic features” are generated from dilations and shiftings of a family of one or more mother wavelet functions. Each atomic feature is used to generate a feature vector element by taking the inner product of the pulse with the atomic feature. The “best” feature vector elements are selected according to the mutual information between the pulse category and feature vector element values over all pulse realizations. The result is a low dimensional transformation that retains the information necessary to discriminate one category from another. This paper presents an algorithm for computing the above mutual information measure on a CNAPS, a 512 processor SIMD parallel computer
Keywords :
parallel algorithms; pattern classification; signal representation; atomic features; dilations; feature selection; feature vector element; inner product; low dimensional representation; low dimensional transformation; mother wavelet functions; mutual information measure; parallel algorithm; pulse classification; shiftings; Concurrent computing; Electronic warfare; Entropy; Laboratories; Mutual information; Noise measurement; Pulse generation; Pulse measurements; Random variables; Stochastic processes;
Conference_Titel :
Time-Frequency and Time-Scale Analysis, 1996., Proceedings of the IEEE-SP International Symposium on
Conference_Location :
Paris
Print_ISBN :
0-7803-3512-0
DOI :
10.1109/TFSA.1996.547460