Computationally efficient architectures of multirate recursive filters are presented in this thesis. An analytical transformation is introduced that converts an IIR filter into an efficient decimation/interpolation filter. The transformation is named as merged delay transformation. This transformation is applicable to first order and second order recursive difference equations. The transfer function of the transformed filter is expressed in the form of H(z M ) so that noble identity of multirate signal processing may be invoked. An N th order filter is required to be implemented in parallel using first order and second order sections. In case of decimation, a down sampler follows an anti-aliasing filter. With the help of merged delay transformation, the filter is transformed and arranged to provide filtering and down sampling in the same stage. This is possible if the filter is implemented in parallel form. Architecture is introduced where down samplers and delays are arranged on the input side. A commutator switch model operating at an M-times higher rate than the output can replace the input down samplers with successive delays. This results in M-to-1 sample rate reduction without changing the filter characteristics. The frequency response and stability of the filter is not disturbed. In case of interpolation, an up sampler precedes an anti-imaging filter. Using merged delay transformation we are able to arrange the up samplers after the sub-filters in parallel paths with successive delays. The up samplers and delays are implemented by a commutator switch model operating at L-times faster rate EFFICIENT ARCHITECTURAL TRANSFORMATION OF MULTIRATE RECURSIVE FILTERS Ph.D Thesis UET, Taxila. 2008 12than the input. Output sampling rate is increased by L and 1-to-L interpolation is achieved. The stability and filter characteristics are unchanged. Filtering and sample rate changes are achieved in the same stage. This avoids the chain of integrators and differentiators as required in a variety of cascade integrator comb (CIC) architectures. Computational costs in terms of number of multiplies per output sample are compared with polyphase FIR structures and IIR structures. The cost reduction increases with increasing values of M or L. For M = 10, the reduction in cost is 82.64% as compared to FIR decimation filters. As compared to IIR structures, the reduction of the order of 48% is achieved. In case of interpolation, the cost reduction is of the order of 45% as compared to polyphase IIR structures. The reduction in cost is about 68% as compared to polyphase FIR. The transformed filters are implemented in Verilog HDL and mapped to an FPGA of Spartan-II technology. Parallel implementation of the filters provides benefits of parallel processing. Increased throughput and less hardware requirement are the important characteristics of this architecture. The technique is expected to find wide use in multirate signal processing such as efficient sample rate conversion from CD’s to Digital Audio Tape and Digital Transmitter/Receivers