Over the last twenty years, combination of adaptive filters has emerged to provide a potential solution in the development of advanced applications, such as channel equalization, active noise control, acoustic echo cancelation, adaptive beamforming, among others. Several authors have demonstrated that the combination of two filters with complementary capabilities improves the overall filter performance in comparison when a single filter is used. Commonly, these combinations employ a fast filter and slow filter to guarantee fast convergence speed and low steady-state mean square error (MSE), respectively, at the cost of increasing their computational complexity. However, those combinations have not been well analysed and compared. Currently, this aspect is crucial since most of the current convex combination of adaptive filters could be implemented in advanced embedded digital devices to be used in real-time signal processing applications. In this work, we evaluate the convex combination of adaptive filters, mainly including those based on least mean square (LMS) algorithm, the affine projection (AP) algorithm and the recursive least mean square (RLS) algorithm. We carry out an extensive performance evaluation to demonstrate the advantages and disadvantages of each approach. Specifically, we simulate them in fixed point, which makes feasible the rapid development of advanced prototypes. This aspect could be potentially valuable to the signal processing engineering communities.

Intradialytic hypotension occurs in 10–30% of hemodialysis (HD) sessions. This phenomenon affects the cardiovascular system’s functions, which are reflected in the activity of the autonomic nervous system (ANS). To indirectly assess the ANS during HD, we analyzed the mean R–R intervals and the spectral power of heart rate variability (HRV) from 20 end-stage renal disease patients divided into hypotensive and non-hypotensive groups. The spectrotemporal analysis was accomplished using short-time Fourier transform with 10 min epochs of HRV overlapping by 40%. The spectral power was divided into three segments according to high frequency, low frequency, and very low frequency bandwidths and averaged to fit quadratic regression models. The analysis of the mean R–R intervals showed significant differences between the groups (p = 0.029). The power variation over time was significant in each spectral band (p ≪ 0.05). The average power, maximum power, and time when the peak was reached differed for each band and between groups, showing the ability to correctly identify the decompensation of the ANS and discriminate between hypotensive and non-hypotensive patients. Additionally, the changes in the sympathovagal ratio were not significant and very scattered for the hypotensive group (p = 0.23) compared to the non-hypotensive group, where the changes were significant (p ≪ 0.05) and much less scattered.

Affine projection (AP) algorithms have been demonstrated to have faster convergence speeds than the conventional least mean square (LMS) algorithms. However, LMS algorithms exhibit smaller steady-state mean square errors (MSEs) when compared with affine projection (AP) algorithms. Recently, several authors have proposed alternative methods based on convex combinations to improve the steady-state MSE of AP algorithms, even with the increased computational cost from the simultaneous use of two filters. In this paper, we present an alternative method based on an affine projection-like (APL-I) algorithm and least mean square (LMS) algorithm to solve the ANC under stationary Gaussian noise environments. In particular, we propose a switching filter selection criteria to improve the steady-state MSE without increasing the computational cost when compared with existing models. Here, we validate the proposed strategy in a single and a multichannel system, with and without automatically adjusting the scaling factor of the APL-I algorithm. The results demonstrate that the proposed scheme exploits the best features of each filter (APL-I and LMS) to guarantee rapid convergence with a low steady-state MSE. Additionally, the proposed approach demands a low computational burden compared with existing convex combination approaches, which will potentially lead to the development of real-time ANC applications.

Presently, the technology development trend of active noise control (ANC) systems is focused on implementing advanced adaptive filters in resource-constrained electronic appliances. Recently, several authors have proved that the use of two adaptive filter algorithms significantly improves the overall adaptive filter performance. However, the computational cost of these approaches is significantly increased since they use two filters simultaneously. Consequently, these filters cannot be implemented in these devices. To solve this problem, we propose a new ANC structure with switching selection based on filtered-x normalized least mean square (FxNLMS) and filtered-x sign least mean square (FxSLMS) algorithms to reduce the computational cost of the ANC system. The improvement of this factor has allowed us to introduce for the first time an advanced spike-based architecture, which can perform dual filter operations using dynamic routing, to be used in real ANC applications. The results have demonstrated that the computational cost of the proposed dual D-FxNLMS/SLMS algorithm is lower compared with previously reported solutions.

Capacitive technology for wireless power transmission has been shown to be a good option for charging the batteries of electric vehicles. It offers better coupling between the transmitter and the receiver than inductive power transmission. On the other hand, it has some disadvantages; for example, it is very sensitive to the distance between plates. Several ideas have recently been proposed to overcome this disadvantage. However, a proper analysis methodology is still lacking, as is a proper design procedure for the circuits used in capacitive transmission. In this paper, an analysis and design methodology is presented for applying the Z-tank resonant circuit to capacitive power transmission, and the theoretical design methodology is based on normalized equations with respect to the operating resonance frequency. The analysis methodology and design procedure result in a circuit where the resonance frequency remains constant despite changes in the distance between the capacitive plates. The simulation results validate the proposal; to ensure robust, realistic simulation results, parasitic elements were considered in all reactive components, and robust models were built for the switching elements, such as MOSFETs and diodes. The results show that the multi-resonant characteristic of the circuit achieves maximum energy transfer and high efficiency.