adaptivefilters are prevalent in many real-time signal processing applications. Many adaptivealgorithms already exist, but most of them assume white Gaussian noise as disturbance. However, for many applications such...
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adaptivefilters are prevalent in many real-time signal processing applications. Many adaptivealgorithms already exist, but most of them assume white Gaussian noise as disturbance. However, for many applications such as electrocardiogram, foetus heart rate measurement, low frequency atmospheric noise, underwater acoustic noise and signal measurement in instrumentation, the impulsive noise is more common. This study presents a modified robust mixed norm (mrmn) adaptivefilteralgorithm robust to impulsive noise with higher convergence rate and lower steady state error (SSE). mrmn adaptive filter algorithm has been simulated using Matlab and Xilinx system generator high level synthesis tool and a significant improvement in SSE and convergence speed is obtained compared with the existing adaptivefilteralgorithms for similar specifications. The proposed algorithm is also described using VHDL and synthesised using Xilinx synthesiser tool in order to implement on field-programmable gate array (FPGA). The FPGA post route and place implementation results show nearly 90% reduction in resource utilisation and nearly 2.6 times improvement in clock frequency as compared with the existing FPGA based implementation for similar specifications.
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