Efficient Adaptive FIR Filter Design Based On CSA

Most of all the algorithms in signal processing involve DA for computing the inner product of two vectors consisting of most of the computational workload. Because of which the DA is widely used in the signal processing algorithms. Using the adders and multipliers the evaluation of the inner product is done. Using DA these multipliers can be replaced for obtaining better performance by reducing the computational workload. Most of all the algorithms in signal processing involve DA for computing the inner product of two vectors consisting of most of the computational workload. Because of which the DA is widely used in the signal processing algorithms. Using the adders and multipliers the evaluation of the inner product is done. Using DA these multipliers can be replaced for obtaining better performance by reducing the computational workload. The main cause for reduction is done due to the pre computation of the partial sum of the coefficients of filter in LUT. Due to which the DA will have fewer arithmetic resources without multipliers. DA based Adaptive filters are widely used in several digital signal processing (DSP) applications. Kairoju Ramachary et.al [03] proposed an efficient method called Least Mean Square for cancellation of noise in electrocardiographic signals. The proposed methodology uses block based error non linear signed regressive LMS algorithm for increasing the convergence speed of the stationary signals for good tracking capability in non stationary signals. The implementation is done in Xilinx tool. Wasim Maroofi et.al [04] presented different pipeline architecture for low power implementation of Adaptive filter using DA. The design swapped by conditional signed carry save accumulator instead of the traditional adder based shift accumulator for DA based Computation of the inner product for obtaining good efficiency with reduced power consumption. Jyothirmayi Alahari et.al [10] delegated a novel approach of pipelined architecture implementation of the Adaptive filter using DA for to get high throughput with less power and area. By updating the LUT the increase in throughput is done. For reduction of area complexity and sampling period conditional signed carry save accumulation is used. The proposed approach used efficient method for Adaptive filter design using Abstract: A novel approach for adaptive filter based on distributed arithmetic (DA) to get high throughput using low area implementation is done. The achieved throughput rate of the proposed design is increased by the use of lookup table (LUT) update, weight update operations and Filtering implementation. For the reduction of the sampling period and area complexity the conventional adder based shift accumulator is replaced by the conventional adder based shift accumulator. Using fast bit-clock for carry-save accumulation with slower clock for all other operations reduction of power consumption is done in the proposed system. The design made use of half the number of multiplexers, smaller LUT and adders when compared to the existing system.