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IMPROVED LMS adaptive algorithm FOR NARROW-BAND INTERFERENCE SUPPRESSION IN DIRECT-SEQUENCE SPREAD-SPECTRUM

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 1995年第3期31卷 1198-1201页

作者： KALIDAS, P PRABHU, KMM INDIAN INST TECHNOL DEPT ELECT ENGNMADRAS 600036TAMIL NADUINDIA

In 1930 Vijayan and Poor proposed nonlinear predictive methods for suppressing narrowband interference in spread spectrum (SS) systems with a significant increase in signal-to-noise ratio (SNR) improvement. The main drawback of their adaptive nonlinear filter is its slow convergence rate. A new adaptive least mean squares (LMS) algorithm to increase the slow convergence rate of their nonlinear adaptive filter is described. Computer simulation results are presented to support the advantages of the new filter.

关键词： Least squares approximation adaptive algorithm Narrowband Convergence Interference suppression Spread spectrum communication Signal to noise ratio Nonlinear filters adaptive filters Computer simulation

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Normalization Method of Gradient Vector in Frequency Domain Steepest Descent Type adaptive algorithm

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2012年第11期E95A卷 2041-2045页

作者： Kuwahara, Yusuke Iwamatsu, Yusuke Fujii, Kensaku Muneyasu, Mitsuji Morimoto, Masakazu Univ Hyogo Grad Sch Engn Himeji Hyogo 6712280 Japan Kansai Univ Fac Engn Sci Suita Osaka 5648680 Japan

In this paper, we propose a normalization method dividing the gradient vector by the sum of the diagonal and two adjoining elements of the matrix expressing the correlation between the components of the discrete Fourier transform (DFT) of the reference signal used for the identification of unknown system. The proposed method can thereby improve the estimation speed of coefficients of adaptive filter.

关键词： Normalization of gradient vector frequency domain adaptive algorithm discrete Fourier transform linear convolution

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Gradient-based adaptive algorithm with an optimum vector of convergence factors

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 1995年第12期43卷 3039-3042页

作者： Ghavami, M Rupprecht, W NaderEsfahani, S UNIV KAISERSLAUTERN INST COMMUN ENGN W-6750 KAISERSLAUTERN GERMANY UNIV TEHRAN DEPT ELECT ENGN TEHRAN IRAN

In this correspondence, an alternative perspective of adaptive filtering by way of optimization theory is presented. We derive an optimum vector of convergence factors for a general-structure adaptive filter and the gradient algorithm. It is proved that the optimum vector of convergence factors produces a faster convergence compared with the optimum but single convergence factor.

关键词： adaptive algorithm Convergence Image reconstruction Signal resolution adaptive filters Finite impulse response filter Biomedical signal processing IIR filters Electrocardiography Discrete cosine transforms

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Fast adaptive algorithm for image restoration

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-FUNDAMENTAL THEORY AND APPLICATIONS 1999年第1期46卷 216-220页

作者： Xu, GF Bose, T Kober, W Thomas, J Univ Colorado Dept Elect Engn Denver CO 80217 USA Data Fus Corp Westminster CO 80021 USA

An adaptive filtering algorithm based on an Euclidean direction search (EDS) method is presented for image restoration. It is a fast algorithm and has a computational complexity of O(N) for least squares optimization. Computer simulations illustrate that this algorithm is very effective in image restoration. The figures for signal-to-noise ratio improvement (SNRI) produced by this algorithm are comparable to those obtained by using the recently reported sample-based conjugate gradient (SCG) algorithm, which has a computational complexity of O(N-2). This algorithm can also he extended to other applications in adaptive signal processing.

关键词： adaptive algorithm Image restoration Signal processing algorithms Computational complexity adaptive filters Filtering algorithms Least squares methods Computer simulation Signal to noise ratio adaptive signal processing

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A ROUNDOFF ERROR ANALYSIS OF THE LMS adaptive algorithm

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IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING 1984年第1期32卷 34-41页

作者： CARAISCOS, C LIU, B Department of Electrical Engineering and Computer Science Princeton University Princeton NJ USA

The steady state output error of the least mean square (LMS) adaptive algorithm due to the finite precision arithmetic of a digital processor is analyzed. It is found to consist of three terms: 1) the error due to the input data quantization, 2) the error due to the rounding of the arithmetic operations in calculating the filter's output, and 3) the error due to the deviation of the filter's coefficients from the values they take when infinite precision arithmetic is used. The last term is of paricular interest because its mean squared value is inversely proportional to the adaptation step size μ. Both fixed and floating point arithmetics are examined and the expressions for the final mean square error are found to be similar. The relation between the quantization error and the error that occurs when adaptation possibly ceases due to quantization is also investigated.

关键词： Roundoff errors Error analysis algorithm design and analysis Least squares approximation adaptive algorithm Quantization Steady-state Digital arithmetic Floating-point arithmetic Mean square error methods

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Two-channel adaptive algorithm for active noise control system using simultaneous equations method

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ACOUSTICAL SCIENCE AND TECHNOLOGY 2012年第6期33卷 339-347页

作者： Fujii, Kensaku Okamoto, Yutaka Itou, Masahiro Muneyasu, Mitsuji Morimoto, Masakazu Univ Hyogo Div Comp Engn 2167 Shosha Himeji Hyogo 6712280 Japan Kansai Univ Fac Engn Sci Suita Osaka 5648680 Japan

We propose a two-channel adaptive algorithm efficiently utilizing independent components slightly involved in reference signals. In active noise control systems, the conventional methods of adding independent components to the reference signals or deliberately changing the correlation between the reference signals are inapplicable, because the reference signals are only detected by noise detection microphones. We have hence presented an adaptive algorithm that does not require the addition of the independent components or the deliberate change to the reference signals. However, this algorithm has three drawbacks. The first is that one of the convergence conditions is described by unmeasurable signals. The second is that pre-estimation of the reference signal power ratio is required. The third is that unknown acoustic paths cannot be identified when the reference signals have high cross-correlation between different sample times. In this work, we derive a new algorithm without the drawbacks and verify, using computer simulations, that the derived algorithm can successfully identify the unknown acoustic paths. The two-channel active noise control system using the simultaneous equations method is thereby expected to provide a high noise reduction effect.

关键词： adaptive algorithm Cost function Convergence condition Skipping operation Cross-correlation reduction

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The Preventive Effect of Computed Tomography ImageeGuided Electroacupuncture Combined with Continuous Femoral Nerve Block on Deep Vein Thrombosis After Total Knee Arthroplasty Based on an adaptive algorithm

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WORLD NEUROSURGERY 2021年 149卷 362-371页

作者： Guo, Xiangrong Gui, Fen Guo, Meiqin Peng, Junhong Yu, Xianjun Fourth Hosp Wuhan Dept Radiol Wuhan Peoples R China First Hosp Wuhan Dept Urol Wuhan Peoples R China First Hosp Guiyang Dept Cardiol Guiyang Peoples R China

Based on an adaptive algorithm model, this study proposed 2 special model structures of randomized fusion and an optimized convolution kernel and use it for image recognition. The adaptive algorithm model combined image-guided electroacupuncture with a continuous femoral nerve block to prevent deep vein thrombosis after total knee arthroplasty. A total of 200 patients after total knee arthroplasty were randomly divided into 4 groups. We assessed the incidence of postoperative lower limb deep vein thrombosis and platelet count before and after surgery. Electroacupuncture combined with continuous femoral nerve block can reduce the incidence of deep vein thrombosis and has obvious advantages in multimode prevention. The effective analgesia provided by electroacupuncture combined with continuous femoral nerve block relieved postoperative pain. It also enabled patients to participate in joint movement and lower limb muscle strength training as soon as possible, which not only is conducive to postoperative functional recovery, but also reduces the body stress response triggered by pain and the hypercoagulable state. Moreover, electroacupuncture stimulation of electroacupuncture points can reduce the inflammatory edema associated with surgery, improve blood circulation at the surgical site, and activate the body's anticoagulation mechanism. This study provides new ideas and references for formulating multimode prevention and control strategies.

关键词： adaptive algorithm CT imageeguided electroacupuncture Deep vein thrombosis Prevention Knee replacement Nerve block

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A FREQUENCY-DOMAIN IMPLEMENTATION OF THE BLOCK P-VECTOR adaptive algorithm

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IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING 1987年第5期35卷 705-707页

作者： MCKOWN, J RUDE, MJ GRIFFITHS, LJ UNIV SO CALIF DEPT EE SYSTLOS ANGELESCA 90089

The P-vector approximate gradient algorithm is used in place of LMS when the desired signal is not available to the processor. This correspondence presents a frequency-domain implementation for use with single-input adaptive filters in which the coefficients are updated every L samples using the average gradient observed during the block. The development follows closely that presented previously for the LMS algorithm, and is slightly more general in that it is presented for complex time series.

关键词： adaptive algorithm Least squares approximation Space technology Signal processing algorithms Signal processing adaptive filters Filtering Convergence Partitioning algorithms Time domain analysis

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A SIMPLE adaptive algorithm FOR REAL-TIME PROCESSING IN ANTENNA ARRAYS

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PROCEEDINGS OF THE IEEE 1969年第10期57卷 1696-&页

作者： GRIFFITH.LJ Barry Research Corporation Palo Alto CA USA

A new adaptation algorithm designed for real-time data processing in large antenna arrays is presented. The algorithm is used to determine the set of filter coefficients (weights) which minimizes the mean-square error in a multidimensional linear filter. The algorithm forms an estimate of the target signal, which is assumed to be of interest, in the presence of interfering noises. It is assumed that the direction of arrival and spectral density of the target signal are known a priori. No such information is assumed to be available regarding the structure of the interfering noise field. The a priori target information is incorporated directly into the adaptation procedure using a modified gradient descent technique. The mathematical convergence properties of the algorithm are presented and a computer simulation experiment is used as an illustration. It is shown that as the number of iterations becomes large, the expected value of the adaptive solution converges to the minimum mean-square-error solution. It is further shown that the variance of the adapted filter about the optimum solution can be made arbitrarily small by appropriate choice of a scalar constant in the algorithm. These results are based on the assumption that the array signals are Gaussian and that successive time samples are statistically uncorrelated. Thus, the new algorithm is shown to converge to the optimum processor in the limit as the number of adaptations becomes large. Any disadvantage which may arise in the use of such an asymptotically optimum system is offset by the extreme simplicity of the adaptive procedure. This simplicity should prove to be particularly useful in many of the practical array processing problems recently encountered in seismic and sonar data processing.

关键词： adaptive arrays adaptive algorithm Antenna arrays Nonlinear filters Data processing algorithm design and analysis Multidimensional systems Computer simulation Array signal processing Sonar

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AN adaptive algorithm FOR STABLE DECISION-FEEDBACK FILTERING

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-ANALOG AND DIGITAL SIGNAL PROCESSING 1993年第1期40卷 1-9页

作者： DOHERTY, JF MAMMONE, RJ RUTGERS UNIV DEPT ELECT & COMP ENGNPISCATAWAYNJ 08854

A new method of decision-feedback filtering is introduced in this paper. The new method is shown to be particularly well suited for data that have undergone spectral nulling. The lack of spectral content causes a large eigenvalue spread of the data correlation matrix. This condition has deleterious effects on the performance of conventional adaptive algorithms, primarily numerical instability and noise amplification. This paper presents an adaptive decision-feedback equalizer update algorithm that does not have these undesirable properties. The algorithm calculates an iterative regularized inverse solution for the decision-feedback equalizer coefficients and applies appropriate attenuation (regularization) at frequencies lacking signal energy. This automatic estimation of the significant signal components is an improvement over other methods that use matrix arithmetic to perform the same task. The other features of the algorithm are linear computational complexity and fast tracking capability. Simulation results are presented that compare the algorithm to the conventional LMS and RLS algorithms for fractionally spaced decision-feedback filtering of a time-varying multipath communication channel.

关键词： adaptive algorithm adaptive filters Iterative algorithms Filtering Decision feedback equalizers Eigenvalues and eigenfunctions Attenuation Frequency Arithmetic Computational complexity

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