By the use of cross-correlation measures, the response of a symmetric Schmitt trigger (ST) driven by a random binary signal and white Gaussian noise is investigated. The results show that the information transmission...By the use of cross-correlation measures, the response of a symmetric Schmitt trigger (ST) driven by a random binary signal and white Gaussian noise is investigated. The results show that the information transmission can be enhanced when a certain amount of noise is presented, i.e., aperiodic stochastic resonance (ASR). Then, the influence of signal amplitude and the ST threshold on ASR is examined, the applicability of the ST in reducing the noise level of random signal transmission and improving the quality of output signal via ASR effect is illustrated. This research is of great interest in the field of digital communications.展开更多
A novel real coded improved genetic algorithm (GA) of training feed forward neural network is proposed to realize nonlinear system forecast. The improved GA employs a generation alternation model based the minimal gen...A novel real coded improved genetic algorithm (GA) of training feed forward neural network is proposed to realize nonlinear system forecast. The improved GA employs a generation alternation model based the minimal generation gap (MGP) and blend crossover operators (BLX α). Compared with traditional GA implemented in binary number, the processing time of the improved GA is faster because coding and decoding are unnecessary. In addition, it needn t set parameters such as the probability value of crossove...展开更多
文摘By the use of cross-correlation measures, the response of a symmetric Schmitt trigger (ST) driven by a random binary signal and white Gaussian noise is investigated. The results show that the information transmission can be enhanced when a certain amount of noise is presented, i.e., aperiodic stochastic resonance (ASR). Then, the influence of signal amplitude and the ST threshold on ASR is examined, the applicability of the ST in reducing the noise level of random signal transmission and improving the quality of output signal via ASR effect is illustrated. This research is of great interest in the field of digital communications.
文摘A novel real coded improved genetic algorithm (GA) of training feed forward neural network is proposed to realize nonlinear system forecast. The improved GA employs a generation alternation model based the minimal generation gap (MGP) and blend crossover operators (BLX α). Compared with traditional GA implemented in binary number, the processing time of the improved GA is faster because coding and decoding are unnecessary. In addition, it needn t set parameters such as the probability value of crossove...
