Finite-precision Goertzel filters used for signal tone detection

2001 ◽  
Vol 48 (7) ◽  
pp. 691-700 ◽  
Author(s):  
R. Beck ◽  
A.G. Dempster ◽  
I. Kale
Keyword(s):  
Finite Precision ◽  
Signal Tone ◽  
Tone Detection

Realization of Signal Tone Detection in Power Line Carrier Terminal

2015 ◽  
Vol 719-720 ◽  
pp. 857-861
Author(s):  
Zhi Ru Gu ◽  
Da Wei Liu ◽  
Hong Li Liu ◽  
Kun Xu
Keyword(s):  
Detection Algorithm ◽  
Power Line ◽  
Theoretical Evaluation ◽  
Nc System ◽  
Time Frequency ◽  
Time Domain Signal ◽  
Power Line Carrier ◽  
Downlink Signal ◽  
Signal Tone ◽  
Tone Detection

—when the noise cancellation system ( NC ) is used in the down link of the power line carrier terminal, it can cancel the background noise and narrowband interference, but the downlink signal tone distorts at the same time. This is because the VAD algorithm of the NC system is sensitive to dramatic changes in the power of signal tone. Through detailed researches on time frequency characteristics of signal tone and error factors of network transmission, a new signal tone detection algorithm that applicable to downlink NC system was put forward, The algorithm detects signal tones through changes of frequency-domain power and time-domain signal period of every frame. After theoretical evaluation and practice tests, it is observed that the above-mentioned algorithm can correctly detect signal tones without influence on functions of the NC system, so as to avoid the occurrence of distortion.

Soft Computing Simulations of Chaotic Systems

2019 ◽  
Vol 29 (08) ◽  
pp. 1950112 ◽  
Author(s):  
Erivelton G. Nepomuceno ◽  
Priscila F. S. Guedes ◽  
Alípio M. Barbosa ◽  
Matjaž Perc ◽  
Robert Repnik
Keyword(s):  
Lower Bound ◽  
Soft Computing ◽  
Chaotic System ◽  
Chaotic Systems ◽  
Logistic Map ◽  
Largest Lyapunov Exponent ◽  
Lower And Upper Bounds ◽  
Finite Precision ◽  
Chua Circuit ◽  
Widespread Interest

Soft computing strategies are drawing widespread interest in engineering and science fields, particularly so because of their capacity to reason and learn in a domain of inherent uncertainty, approximation, and unpredictability. However, soft computing research devoted to finite precision effects in chaotic system simulations is still in a nascent stage, and there are ample opportunities for new discoveries. In this paper, we consider the error that is due to finite precision in the simulation of chaotic systems. We present a generalized version of the lower bound error using an arbitrary number of natural interval extensions. The lower bound error has been used to simulate a chaotic system with lower and upper bounds. The width of this interval does not diverge, which is an advantage compared to other techniques. We illustrate our approach on three systems, namely the logistic map, the Singer map and the Chua circuit. Moreover, we validate the method by calculating the largest Lyapunov exponent.

Sign in / Sign up

Export Citation Format

Share Document