Title :
New adaptive detection filters using Newton-type algorithms
Author :
Lindquist, Claude S. ; Shen, Jun
Author_Institution :
Dept. of Electr. & Comput. Eng., Miami Univ., Coral Gables, FL, USA
Abstract :
An adaptive detection filter detects the presence of a desired signal in noisy environment. In this paper, we present several detection filtering algorithms in the time domain. Our algorithm´s vector forms are compared with gradient search methods include Newton, steepest descent and least-mean-square. We find that our algorithms are of the Newton-type
Keywords :
adaptive filters; filtering and prediction theory; matrix algebra; noise; numerical analysis; signal detection; time-domain analysis; transient response; Newton method; Newton-type algorithms; adaptive detection filters; detection filtering algorithms; gradient search methods; impulse response matrices; least-mean-square; noisy environment; steepest descent method; time domain; Adaptive filters; Adaptive signal detection; Filtering algorithms; Information filtering; Information filters; Matched filters; Matrix converters; Search methods; Signal detection; Working environment noise;
Conference_Titel :
Southeastcon '94. Creative Technology Transfer - A Global Affair., Proceedings of the 1994 IEEE
Conference_Location :
Miami, FL
Print_ISBN :
0-7803-1797-1
DOI :
10.1109/SECON.1994.324345
