The example,Signal Detection in White Gaussian Noise, introduces a basic signal detection problem. In that example, only one sample of the received signal is used to perform the detection. This example involves more samples in the detection process to improve the detection performance. ...
Gaussian Random VectorTrigonometric SystemWe consider the problem of signal detection in the heteroscedastic Gaussian white noise when the set of alternatives is essentially nonparametric. In this setting, we find a family of asymptotically minimax tests. The results are extended to the case of testing...
Optimal detection of a known FSK-modulated binary signal in additive white Gaussian noise using a matched filter receiver requires knowledge of second-order noise statistics. The dependence on noise statistics causes the probability of detection to be sensitive to errors in the noise variance value. ...
Signal detection in additive white Gaussian noise (AWGN) is one of the long-term developments driving the evolution of many different fields of science and technology, with important applications in telecommunications, medicine and astronomy. In this paper, we propose a novel method of blind signal...
A discussion of the dominant errors is presented including picosecond pulse generator jitter, sampling clock jitter, sampling rate, and system additive white Gaussian noise. We show a simple method to calculate the total system jitter, and describe error biasing phenomenon as the tag moves, ...
The detection of weak transient signal buried in non-Gaussian noise is investigated. Non-Gaussian noise is modeled by Gaussian mixture distribution. 3-level quantizer is used as a nondynamic stochastic resonance method to enhance SNR of weak signal. NL-length samples of signal are arranged into ...
HOS-based symmetric and asymmetric statistical models of non-Gaussian noise for signal detection optimization * In the context of digital signal processing addressed to communications, this work focuses attention on the optimization of detection of weak signals in presence of additive independent stationary...
The point here is that, in spite of the fact that the observation vector can be very large, the decision statistic is a single number, the sufficient statistic. The detection parameter d now becomes (18)d=2E/N0. The quantity 2E/N0 is the signal-to-noise ratio. Here, it is to be ...
In addition, the effects of the time-delayed feedback on the theoretical chaotic threshold are investigated under Gaussian white noise based on the Langevin and the Melnikov function. The time-delayed feedback τ can reduce the theoretical chaotic threshold, which is beneficial to detect the weak ...
Finally, experimental results are given. The results show that block hidden Markov model (BHMM) is a powerful yet simple tool in signal denoising. 展开 关键词: block hidden Markov model additive Gaussian white noise wavelet transform DOI: 10.1142/S0218001405004265 被引量: 6 年份: 2008 ...