The adaptive filter constitutes an important part of statistical signal processing. Adaptive filters are often realized either as a set of program instructions running on an arithmetical processing device such as a Microprocessor or Digital Signal Processing (DSP) chip, or as a set of logic operations implemented in a field programmable gate array (FPGA) or in Very Large Scale Integrated Circuit (VLSI). Systolic architecture improves the speed of the system at the cost of increased area. On the other hand, folding technique uses less hardware resources. A combination of systolic and folding structures provides improvement in speed and reduction in area. This paper presents a novel idea of combining Systolic and Folding architectures and its design in various adaptive filters like Recursive Least Square (RLS), Affine Projection (AP) and Kalman filters. The structures are designed using Xilinx System Generator tool of MATlab 2015 and implemented in Xilinx Virtex 5 FPGA. The designed structures are tested for noise cancellation in Electrocardiogram (ECG) signal and results are analysed for various order of all the filters and its metrics are analysed in terms of Signal to Noise Ratio(SNR), Mean Square Error(MSE), area and speed. From the analysis it is observed that the proposed folding in systolic structures improves SNR by 6.77% in RLS, 4.68% in Affine projection and 2.13% in Kalman Algorithm than the conventional structures. It is inferred that the proposed design in Affine projection shows improved SNR than the other filters. The proposed combined folding in systolic architecture shows 18.35% reduction in area and reduction in delay.