Design of twodimensional digital filters using neural networks

A new approach for the design of two-dimensional （2-D） linear phase FIR digital filters based on a new neural networks algorithm （NNA） is provided. A compact expression for the transfer function of a 2-D linear phase FIR filter is derived based on its frequency response characteristic, and the NNA, based on minimizing the square-error in the frequency-domain, is established according to the compact expression. To illustrate the stability of the NNA, the convergence theorem is presented and proved. Design examples are also given, and the results show that the ripple is considerably small in passband and stopband, and the NNA-based method is of powerful stability and requires quite little amount of computations.

基于布谷鸟优化算法的二维FIR数滤字波器设计

针对二维(2-D)有限冲击长响应(FIR)数字滤波器设计中的传输函数,提出了一个基于布谷鸟优化算法的传输函相位区间优化设计算法,该算法在McClellan变换下通过布谷鸟优化算法搜索最小的传输函相位区间均方误差,所产生的新解既可以继承当前最优解,又可以不局限于局部最优,不但可以解决2-D FIR滤波器设计中非线性的优化问题,而且也能减少滤波器设计的复杂度和数据的溢出问题。最后,以低通扇形和高通椭圆形的2-D FIR滤波器为例,分别进行了仿真设计实验,结果表明,在相同的规定通带和阻带衰减等参数条件下,该优化算法与已有算法相比,滤波器传输系数的向量误差可降低4.9%-27%,阻带衰减起伏也随之减少。