Title :
A neural network tunable filter for multi-tone detection
Author :
Rao, Sathyanarayan S. ; Sethuraman, Sriram
Author_Institution :
Dept. of Electr. Eng., Villanova Univ., PA, USA
Abstract :
A neural network that tunes to a band of frequencies depending on its inputs is proposed as a preprocessor for multiple sinusoid detection and estimation in additive noise. The multilayer perceptron network is trained off-line using the standard backpropagation algorithm. The authors provide a logical development of the problem and discuss the advantages of the proposed scheme. Potential applications in communications are cited, and Monte Carlo simulation results are presented
Keywords :
digital filters; feedforward neural nets; signal detection; signal processing; tuning; Monte Carlo simulation; additive noise; backpropagation algorithm; communications; multilayer perceptron network; multiple sinusoid detection; multiple sinusoid estimation; multitone detection; neural network tunable filter; preprocessor; signal processing; Additive noise; Band pass filters; Data preprocessing; Filter bank; Frequency estimation; Frequency shift keying; Neural networks; Noise reduction; Signal processing; Signal to noise ratio;
Conference_Titel :
Military Communications Conference, 1992. MILCOM '92, Conference Record. Communications - Fusing Command, Control and Intelligence., IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-0585-X
DOI :
10.1109/MILCOM.1992.243998
