This paper presents two new, closely related adaptive algorithms for LS system identification. The starting point for the derivation of the algorithms is the inverse Cholesky factor of the data correlation matrix, obt...
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ISBN:
(纸本)0780324323
This paper presents two new, closely related adaptive algorithms for LS system identification. The starting point for the derivation of the algorithms is the inverse Cholesky factor of the data correlation matrix, obtained via a QR decomposition (QRD). Both are of O(p) computational complexity with p being the order of the system. The first algorithm is a fixed order QRD scheme with enhanced parallelism. The second is a lattice type algorithm based on Givens rotations, with lower complexity compared to previously derived ones.
In this paper, the performance of LMS and RLS adaptive algorithms for optimum combining applied to the reverse link of W-CDMA is studied in terms of SINR and computational load. Results are shown for different antenna...
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ISBN:
(纸本)0780374673
In this paper, the performance of LMS and RLS adaptive algorithms for optimum combining applied to the reverse link of W-CDMA is studied in terms of SINR and computational load. Results are shown for different antenna arrays configurations in the base station site (number and separation between antenna elements, individual radiation patterns) and system scenarios (number and azimuthal distribution of users). Special emphasis is made on the antenna structure, and on the algorithms complexity, practical implementation and performance.
This papers describes a new, fast and economical methodology to test linear analog circuits based on adaptive algorithms. To the authors knowledge, this is the first time such technique is used to test analog circuits...
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ISBN:
(纸本)0897919645
This papers describes a new, fast and economical methodology to test linear analog circuits based on adaptive algorithms. To the authors knowledge, this is the first time such technique is used to test analog circuits, allowing complete fault coverage. The paper presents experimental results showing easy detection of soft, large-deviation and hard faults, with low cost instrumentation. Components variations from 5% to 1% have been detected, as the comparison parameter (output error power) varied from 300% to 20%.
Recently, a sparse adaptive algorithm termed zero-attracting sign least-mean-square (ZA-SLMS), has been clarified to be able to reconstruct robustly heartbeat spectrum by Doppler radar signal. However, since the stren...
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ISBN:
(纸本)9781538636466
Recently, a sparse adaptive algorithm termed zero-attracting sign least-mean-square (ZA-SLMS), has been clarified to be able to reconstruct robustly heartbeat spectrum by Doppler radar signal. However, since the strengths of noise evidently differ under different body motions, the sparse heartbeat spectra cannot be always acquired accurately by the constant regularization parameter (REPA) that balances the gradient correction and the sparse penalty, applying in the ZA-SLMS algorithm. In this paper, an improved ZA-SLMS algorithm is proposed by introducing adaptive REPA (AREPA), where the proportion of sparse penalty is adjusted based on the standard deviation of radar data. Moreover, to enhance the stability of heartbeat detection, a time-window-variation (TWV) technique is further introduced in the improved ZA-SLMS algorithm, considering the fact that the position of spectral peak associated with the heart rate (HR) is stable when the length of time window changes within a short period. Experimental results measured against five subjects validated that our proposal reliably improves the error of HR estimation than the standard ZA-SLMS algorithm.
The l(0)-Least Mean Squares (l(0)-LMS) and l(0)-Normalized LMS (l(0)-NLMS) are arguably the best among gradient adaptive algorithms for sparse system identification. However, due to the non-linear and non-convex spars...
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ISBN:
(纸本)9781509009169
The l(0)-Least Mean Squares (l(0)-LMS) and l(0)-Normalized LMS (l(0)-NLMS) are arguably the best among gradient adaptive algorithms for sparse system identification. However, due to the non-linear and non-convex sparse penalty term in their cost functions, deriving analytical modals for the Mean Square Deviation (MSD) update equation is quiet challenging. In this paper, the significant and zero taps misalignment is studied separately, and then joined in a dynamical manner. Thus, we propose the MSD update equations for both l(0)-LMS and l(0)-NLMS, with reasonable assumptions for white input signal. Moreover, the steady state MSD of both algorithms is presented. Simulation results illustrate strong agreement between the derived analytical modals and the empirical simulation.
It is well known that most adaptive filtering algorithms are developed based on the methods of least mean squares or of least squares. The popular adaptive algorithms such like the LMS, the RLS and their variants have...
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ISBN:
(纸本)9781424421091
It is well known that most adaptive filtering algorithms are developed based on the methods of least mean squares or of least squares. The popular adaptive algorithms such like the LMS, the RLS and their variants have been developed for different applications. In this paper, we propose to use maximum a posteriori (MAP) probability approach to estimate the filter coefficients. We show that the RLS, LMS and their variants based on the MAP method are in fact particular cases where the models of the filtering errors and the filter coefficients are with different probability density functions. We can further explore new adaptive algorithms within MAP framework.
作者：
Bhouri, MUniv Paris 05
Ctr Univ St Peres UFR Math & Informat F-75270 Paris 06 France
In this paper we extend the QR-based recursive least squares algorithms to a more general square-root formulation, which involves array transform using orthogonal and possibly non orthogonal transforms e.g. Gauss tran...
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ISBN:
(纸本)0780362934
In this paper we extend the QR-based recursive least squares algorithms to a more general square-root formulation, which involves array transform using orthogonal and possibly non orthogonal transforms e.g. Gauss transform. The adaptive algorithms, thus obtained, have better numerical properties than the traditional pseudo-inverse-based algorithms. This new update scheme covers an extended set of algorithms it connects the recursive least squares to gradient based algorithms. Moreover, we show that the recently derived Block diagonal QR based algorithms [1][2] belongs to this general square-root class.
We introduce a novel method for analyzing a well known class of adaptive algorithms. By combining recent developments from the theory of Markov processes and long existing results from the theory of Perturbations of L...
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ISBN:
(纸本)0780350006
We introduce a novel method for analyzing a well known class of adaptive algorithms. By combining recent developments from the theory of Markov processes and long existing results from the theory of Perturbations of Linear Operators we study first the behavior and convergence properties of a class of products of random matrices. This in turn allows for the analysis of the first and second order statistics of the adaptive algorithms yielding estimates for the exponential rate of convergence and the covariance matrix of the estimation error.
Ambient energy-powered sensors are becoming increasingly crucial for the sustainability of the Internet-of-Things (IoT). In particular, batteryless sensors are a cost-effective solution that require no battery mainten...
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Ambient energy-powered sensors are becoming increasingly crucial for the sustainability of the Internet-of-Things (IoT). In particular, batteryless sensors are a cost-effective solution that require no battery maintenance, last longer and have greater weatherproofing properties due to the lack of a battery access panel. In this work, we study adaptive transmission algorithms to improve the performance of batteryless IoT sensors based on the LoRa protocol. First, we characterize the device power consumption during sensor measurement and/or transmission events. Then, we consider different scenarios and dynamically tune the most critical network parameters, such as inter-packet transmission time, data redundancy and packet size, to optimize the operation of the device. We design appropriate capacity-based storage, considering a renewable energy source (e.g., photovoltaic panel), and we analyze the probability of energy failures by exploiting both theoretical models and real energy traces. The results can be used as feedback to re-design the device to have an appropriate amount energy storage and meet certain reliability constraints. Finally, a cost analysis is also provided for the energy characteristics of our system, taking into account the dimensioning of both the capacitor and solar panel.
This paper provides a new insight into the smooth and precise adaptive railway transport braking system development. The system contains a controller with a control program based on an adaptive control algorithm and a...
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ISBN:
(纸本)9781479974627
This paper provides a new insight into the smooth and precise adaptive railway transport braking system development. The system contains a controller with a control program based on an adaptive control algorithm and a current train braking control system ensures an automatic smooth and precise braking of a train and another controller ensures an automatic stopping of the train before the red light. Some of the adaptive search algorithms are studied and the task is to test and select the most suitable and the most effective of them. The computer model and simulation results are described in this paper.
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