No abstract

In this paper, least mean square (LMS) adaptive filter and its several variants are used to remove the noise in degraded electrocardiographic (ECG) signals. One of the main interference sources in measurement of ECG signal includes 50 Hz power line that produces distortion in the original signal while measuring. Recently, adaptive filtering is supposed to be one of the most popular and effective methods for the analysis and processing of ECG signals. In this paper comparison has been made and suggests a suitable implementation of the noise canceller for the biotelemetry applications which require high signal to noise (SNR) ratios. These schemes generally involve simple procedures such as shift operations and simple addition and attain effective results as compared to other LMS based realizations.

In recent years, it is been a great challenge to have high data transmission rates with additional bandwidth at the same time in wireless communication systems. Multicarrier systems along with MIMO have provided good results in achieving high bandwidth and spectral efficiency. Recently Filter bank multicarrier systems (FBMC) have been implemented and provided better results in terms of spectral shaping of the subcarriers as compared to the traditional orthogonal frequency division multiplexing (OFDM) with cyclic prefix (CP). Consequently, the major observable difference between the two approaches is in frequency selectivity. In this research, we will present a modified neural network based algorithm (NN) which is based on meansquared error (MSE) trained for MIMO-FBMC systems with QAM modulation (QAM). The algorithm presents a persubchannel adaptive channel equalizer with low complexity. Practical channel information has been used in the simulations. Furthermore, the convergence characteristic curves of NN based equalizer per-subcarrier will be discussed and also how the proposed algorithm will be optimized and evaluated. Moreover, to elaborate equalization concepts more in detail the proposed equalizer will be implemented for classical OFDM-QAM system and results will be compared to the simulations performed for traditional least mean square (LMS) based persubcarrier channel equalizer.