Masker Level and Noise‐Signal Detection

1964 ◽  
Vol 36 (3) ◽  
pp. 570-575 ◽  
Author(s):  
Richard A. Campbell
2021 ◽  
Vol 25 ◽  
pp. 233121652110101
Author(s):  
Dmitry I. Nechaev ◽  
Olga N. Milekhina ◽  
Marina S. Tomozova ◽  
Alexander Y. Supin

The goal of the study was to investigate the role of combination products in the higher ripple-density resolution estimates obtained by discrimination between a spectrally rippled and a nonrippled noise signal than that obtained by discrimination between two rippled signals. To attain this goal, a noise band was used to mask the frequency band of expected low-frequency combination products. A three-alternative forced-choice procedure with adaptive ripple-density variation was used. The mean background (unmasked) ripple-density resolution was 9.8 ripples/oct for rippled reference signals and 21.8 ripples/oct for nonrippled reference signals. Low-frequency maskers reduced the ripple-density resolution. For masker levels from −10 to 10 dB re. signal, the ripple-density resolution for nonrippled reference signals was approximately twice as high as that for rippled reference signals. At a masker level as high as 20 dB re. signal, the ripple-density resolution decreased in both discrimination tasks. This result leads to the conclusion that low-frequency combination products are not responsible for the task-dependent difference in ripple-density resolution estimates.


2013 ◽  
Vol 310 ◽  
pp. 421-423
Author(s):  
Chun Yu Wang ◽  
Xing Long Qi ◽  
Run Lan Tian ◽  
Lin Ren

Radar signal detection theory is significant for the radar signal detection, and there are many radar signal detection method at present. In this paper, higher order statistics was used to achieve the radar signal detection. It analyzed the basic theory of higher order statistics and higher order statistics in radar signal detection. And it achieved radar signal detection in the MATLAB software, colored Gaussian noise signal detection method based on dual-spectrum was used to detect the radar signal mixed with man-made noise.


2021 ◽  
Vol 2074 (1) ◽  
pp. 012055
Author(s):  
Naibin Zhai ◽  
Haijun Zhao ◽  
Xintao Cui

Abstract As an important part of vehicle noise signal detection and processing, negative entropy detection algorithm can accurately reduce the number of speech coding bits, ameliorate the recognition accuracy, and establish the noise model in the process of noise reduction. Based on this, this paper first analyses the source and control of vehicle vibration and noise, then studies the principle of negative entropy detection algorithm of vehicle vibration and noise signal, and finally gives the vehicle vibration and noise signal detection method based on negative entropy detection algorithm.


2010 ◽  
Vol 174 ◽  
pp. 311-314
Author(s):  
Ji Fei Cai ◽  
Yuan Huang ◽  
Xin Zhu Wang

To improve the stability of a Paper-Transferring Mechanism (PTM), a profound understanding must be made on its vibration characteristics, on which based, a modified design was made. Through kinetic and dynamic analysis of the PTM, the natural frequencies were obtained based on the vibration signal detection and noise signal analysis. To reduce the vibration response of the PTM, first is to reduce its maximum acceleration and reduce the quality of moving parts and improve its quality distribution, then structural modification to the wallboards and pull beams of the platform should be made to render its inherent frequencies from its working frequencies.


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