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详细研究了3型FIR线性相位滤波器的幅频响应与正弦基函数神经网络算法之间的关系,提出并证明了该模型算法的收敛性定理,给出了3型FIR带通滤波器、海尔伯特变换器和微分器的优化设计实例。研究结果表明提出的算法避免了求高价逆矩阵的困难,有效解决了3型FIR高价数字滤波器优化设计的瓶颈问题。计算机仿真结果表明了正弦基函数神经网络算法在3型FIR高价数字滤波器优化设计领域中的有效性。
The relationship between the amplitude-frequency response of the 3-type FIR linear phase filter and the sinusoidal basis function neural network algorithm is studied in detail. The convergence theorem of this model algorithm is proposed and proved. The 3-type FIR band-pass filter, Burt converter and differentiator optimization design examples. The results show that the proposed algorithm avoids the difficulty of finding high-cost inverse matrices and effectively solves the bottleneck problem of the optimal design of 3-type FIR high-cost digital filters. Computer simulation results show the effectiveness of the sinusoidal basis function neural network algorithm in the field of 3-type FIR high-cost digital filter optimization design.