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This paper presents an algorithm to design jointly interpolation filters and decision feedback equalizers in the sense of minimum mean-square error such that the joint capacity which is neglected in conventional design is explored to improve the receiver performance. The algorithm comprises an iteration of two alternating simple quadratic minimizing operations and ensures convergence. A simulation example for the raised-cosine channel demonstrates that via this approach an improvement over the conventional design can be achieved. Index Terms--Alternating coordinates minimization algorithm, decision feedback equalizers, interpolation filters.

The identification of the model parameters of a high-density recording channel generally requires solution of nonlinear equations. In this paper, we apply the expectation and maximization (EM) algorithm to realize the maximum likelihood estimation of the parameters of a simple partial erasure model, including the reduction parameters and the isolated transition response. The algorithm that results from this approach iteratively solves two least-squares problems and, thus, realization is simple. Computer simulations verify the feasibility of the EM algorithm, and show that the proposed algorithm has fast convergence and the resulting estimator is asymptotically efficient. Index Terms--Expectation and maximization algorithm, least-squares methods, maximum-likelihood estimation, Monte Carlo methods, simple partial erasure model.

The modified discrete cosine transform/inverse modified discrete cosine transform (MDCT/IMDCT) algorithm is examined using a matrix representation.

The identification of model parameters of a high-density recording channel is usually difficult and complicated. In this paper, we successfully apply the alternating coordinates minimization (ACM) algorithm for estimating parameters of a partial erasure plus transition shift model (PETSM). The resulting algorithm turns out to iteratively solve two least square problems and is guaranteed to converge. Furthermore, the obtained model for a nonlinear partial response channel is more accurate than conventional models such that the maximum likelihood (ML) detector has better bit error rate (BER) performance without increasing its realization complexity. Computer simulations show that the ACM algorithm can accurately estimate the model parameters and the BER for the detector is significantly improved especially when the transition shift parameter is large. Index Terms--Alternating coordinates minimization, maximum likelihood detector, partial erasure ratio, partial response channel, transition shift parameter.

This paper presents a real-time maximum-likelihood heart-rate estimator for ECG data measured via wearable textile sensors. The ECG signals measured from wearable dry electrodes are notorious for its susceptibility to interference from the respiration or the motion of wearing person such that the signal quality may degrade dramatically. To overcome these obstacles, in the proposed heart-rate estimator we first employ the subspace approach to remove the wandering baseline, then use a simple nonlinear absolute operation to reduce the high-frequency noise contamination, and finally apply the maximum likelihood estimation technique for estimating the interval of R-R peaks. A parameter derived from the byproduct of maximum likelihood estimation is also proposed as an indicator for signal quality. To achieve the goal of real-time, we develop a simple adaptive algorithm from the numerical power method to realize the subspace filter and apply the fast-Fourier transform (FFT) technique for realization of the correlation technique such that the whole estimator can be implemented in an FPGA system. Experiments are performed to demonstrate the viability of the proposed system.

In this study, we propose a novel design of the wearable digital sensor, embedded within a monitoring suit for posture monitoring. Our studies are going to solve wearable monitoring systems' drawbacks, include non-washable, uncomfortable, and high power -consumption due to complex signal processing. There are two digital sensor designs, dome shape type and clip shape type, knitted on clothes. The characteristics of these two digital sensor designs are easy implementation, small size, low power-consumption, and comfort. Our proposed system can catch up and monitor postures of the real-time information from the wearing person. Therefore, the monitoring system embedded with the capability of detecting real-time postures and transmission makes it highly suitable for applications of remote healthcare and wellness.