The design of peak-constrained least squares FIR filters with low-complexity finite-precision coefficients

A method for the design of peak-constrained least squares (PCLS) finite-impulse response (FIR) digital filters with low-complexity finite-precision coefficients (FPC) based on Adams' optimality criterion and an efficient local search is presented. Simple quantization of the infinite precision coefficients typically leads to filter designs which fail to meet the frequency response, passband to stopband energy ratio (PSR) and coefficient complexity (number of coefficient adders and subtractors) specifications. It is shown that it is possible to design a filter with an acceptable PSR that meets the frequency response specification while using a reduced number of adders and subtractors.