Real time signal detection in communication system with additive non-gaussian noise

1991 ◽  
Vol 74 (6) ◽  
pp. 38-52
Author(s):  
Masaaki Amano
Keyword(s):  
Signal Detection ◽  
Real Time ◽  
Gaussian Noise ◽  
Communication System ◽  
Time Signal ◽  
Non Gaussian

An automatic seismic signal detection algorithm based on the Walsh transform

1981 ◽  
Vol 71 (4) ◽  
pp. 1351-1360
Author(s):  
Tom Goforth ◽  
Eugene Herrin
Keyword(s):  
Signal Detection ◽  
Real Time ◽  
Seismic Signal ◽  
Detection Algorithm ◽  
Machine Language ◽  
Walsh Transform ◽  
Time Signal ◽  
Data Systems ◽  
Detection Capability ◽  
Short Period

abstract An automatic seismic signal detection algorithm based on the Walsh transform has been developed for short-period data sampled at 20 samples/sec. Since the amplitude of Walsh function is either +1 or −1, the Walsh transform can be accomplished in a computer with a series of shifts and fixed-point additions. The savings in computation time makes it possible to compute the Walsh transform and to perform prewhitening and band-pass filtering in the Walsh domain with a microcomputer for use in real-time signal detection. The algorithm was initially programmed in FORTRAN on a Raytheon Data Systems 500 minicomputer. Tests utilizing seismic data recorded in Dallas, Albuquerque, and Norway indicate that the algorithm has a detection capability comparable to a human analyst. Programming of the detection algorithm in machine language on a Z80 microprocessor-based computer has been accomplished; run time on the microcomputer is approximately 110 real time. The detection capability of the Z80 version of the algorithm is not degraded relative to the FORTRAN version.

Signal Detection in Correlated Non-Gaussian Noise Using Higher-Order Statistics

2017 ◽  
Vol 37 (4) ◽  
pp. 1704-1723
Author(s):  
Elena Palahina ◽  
Mária Gamcová ◽  
Iveta Gladišová ◽  
Ján Gamec ◽  
Volodymyr Palahin
Keyword(s):  
Signal Detection ◽  
Order Statistics ◽  
Gaussian Noise ◽  
Higher Order ◽  
Higher Order Statistics ◽  
Non Gaussian
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