Develops a new iterative reweighted least squares algorithm for the design of optimal L/sub p/ approximation FIR filters. The algorithm combines a variable p technique with a Newton's method to give excellent robust initial convergence and quadratic final convergence. Details of the convergence properties when applied to the L/sub p/ optimization problem are given. The primary purpose of L/sub p/ approximation for filter design is to allow design with different error criteria in pass and stopband and to design constrained L/sub 2/ approximation filters. The new method can also be applied to the complex Chebyshev approximation problem and to the design of 2D FIR filters.
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机译：开发了一种新的迭代加权最小二乘算法，用于设计最佳L / sub p /近似FIR滤波器。该算法将可变p技术与牛顿法相结合，可提供出色的鲁棒初始收敛和二次最终收敛。给出了应用于L / sub p /优化问题时收敛特性的详细信息。 L / sub p /逼近滤波器设计的主要目的是允许通带和阻带设计具有不同的误差标准，并设计约束L / sub 2 /逼近滤波器。新方法还可以应用于复杂的Chebyshev逼近问题和2D FIR滤波器的设计。
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