Design of LMS algorithm for noise canceller based on FPGA

This paper presents the design of an adapting filtering method to remove the noise in the biomedical signal records. The major concern about analyze the presence of various artifacts in ECG records and modular artifacts in EEG records caused due to various noise factors. Here, we have proposed a design based on LMS (Least Mean Square) algorithm to remove the artifacts from biomedical signal using Verilog HDL based on been mapped on  commercially available FPGAs (Field Programmable Gate Arrays). In this design the LMS algorithm used as a noise canceller and the reference signal was adaptively filtered and subtracted from primary signal to obtain the estimated biomedical signal. The original biomedical signal can be reconstructed by passing the digital bit stream through a low pass filter. This design is suitable for its low power biomedical instrument design and it reduces the whole system cost. Keywords: LMS algorithm, noise canceller, Verilog HDL, artifacts, biomedical signal, Low power application

Fusion of chaotic activation functions in training neural network

Multilayer feed-forward neural network is trained with a supervised algorithm which is loosely connected with biological learning. Bio-inspired system development is recently a challenging topic in intelligent system design. To make the learning biologically plausible, we propose 'Fusion of Chaotic Activation Functions' (FCAF) in which multiple chaotic activation functions (AFs) are used to compute final activation. It is to investigate whether FCAF can enable the learning to be faster. Validity of the proposed method is examined by performing simulations on challenging ten real benchmark classification and time series prediction problems. The FCAF has been applied to 2-bit, 3-bit and 4-bit parity, the breast cancer, Diabetes, Heart disease, Glass, Flare, credit card and thyroid problems. The algorithm is shown to work better than other AFs used independently in BP such as sigmoid (SIG), arctangent (ATAN), logarithmic (LOG), and that of jointly such as fusion of activation function (FAF)