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针对通信信号的非线性时域滤波问题,研究了量子随机滤波器的原理和性能.将神经网络与非线性Schroedinger方程相结合,把方程的解作为信号时变的概率密度函数,进而实现滤波功能.研究发现,通过调整势场权系数的取值,可使滤波器具有明显不同的性能.根据此性质,构造了一种新的滤波算法,该算法可使滤波器在信号波形估计的非线性失真程度与它的抗噪能力之间进行折衷,这将大大推广量子随机滤波器的应用,例如,用于通信信号处理.仿真结果表明了量子随机滤波器的优越性能.
Aiming at the nonlinear time-domain filtering problem of communication signal, the principle and performance of quantum random filter are studied. Combining neural network and nonlinear Schroedinger equation, the solution of the equation is taken as the probability density function of time-varying signal, and then the filtering function The study found that by adjusting the value of the potential coefficient of the potential field, the filter can have significantly different performance.Based on this property, a new filtering algorithm is constructed, which can make the filter nonlinear in the signal waveform estimation The trade-off between the degree of distortion and its noise immunity will greatly promote the use of quantum random filters, for example, for communication signal processing.The simulation results show the superior performance of the quantum random filter.