Convergence in Mean Square
Reyni’s Entropy and Mean Square Error for Improving the Convergence of Multilayer Backprobagation Neural Networks : A Comparative Study
... and convergence rate of the Multilayer Backpropagation Neural Network Algorithms is an active area of ...and convergence rate of multilayer Backpropagation (BP) Neural Networks was ...usual mean ...
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A Two-Stage Approach for Improving the Convergence of Least-Mean-Square Adaptive Decision-Feedback Equalizers in the Presence of Severe Narrowband Interference
... the mean- squared error [11] (or equivalently by solving the Wiener- Hopf ...least- mean square (LMS) algorithm ...slow convergence when there is a large disparity in the eigenvalues of the ...
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Approximation of multidimensional stochastic processes from average sampling
... the convergence property of sampling series, the estimate of truncation error in the mean square sense and the almost sure results on sampling the- orem for multidimensional random signals from ...
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Convergence and stability of the exponential Euler method for semi linear stochastic delay differential equations
... strong convergence and exponential stability in mean square of the exponential Euler method to semi-linear stochastic delay differential equations ...
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Least Mean Square (LMS) for Smart Antenna
... where y(n) is the filter output, e(n) is the error signal between filter output and desired signal d(n) at time n, and u(n) is the transmitted signal. In addition, w (n) is the update function for the LMS algorithm, ...
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Comparative Study of Adaptive Filter Algorithm of a QO-STBC Encoded MIMO CDMA System
... In this study MATLAB-SIMULINK based QO-STBC encoded MIMO CDMA system for LMS, NLMS and RLS adaptive filter algorithms are compared on the basis of convergence speed and root mean square error (RMSE). ...
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Comparison of Beam forming algorithms for better Convergence
... least mean square (VSSNLMS) and Normalised least mean square(NLMS) with respect to mean square error for various cases by varying the number of interference users and number of ...
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New Behavior Model and Adaptive Predistortion for Power Amplifiers
... least mean square) algorithm is a class of LMS algorithms with variable step sizes, which overcomes the contradiction between convergence speed and the steady-state error of fixed step size ...
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A NEW ADAPTIVE BEAMFORMING ALGORITHM FOR SMART ANTENNA
... least mean square (NM-NLMS) algorithm to improve interference suppression in adaptive beam forming smart antenna ...fast convergence rate, higher interference suppression capability and low level of ...
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A Low Delay and Fast Converging Improved Proportionate Algorithm for Sparse System Identification
... fast convergence of the improved proportionate normalized least mean square (IPNLMS) algorithm and the efficient implementation of the multidelay adaptive filtering (MDF) algorithm inheriting the ...
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DUAL CHANNEL SPEECH ENHANCEMENT USING HADAMARD- LMS ALGORITHM WITH DCT PREPROCESSING TECHNIQUE
... least mean square (LMS) algorithm is very popular because of its simplicity and easy of ...its convergence rate is highly dependent on the feedback coefficient μ and the input power to the adaptive ...
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A Fast convergent frequency domain MIMO equalizer for few mode fiber communication systems
... the Mean Square Error Convergence performance, evolution of weights and the hardware complexity comparison of both the Benveniste and Adaptive Regularization algorithm and observed that the evolution ...
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Statistical Study of Least Mean Square and Normalised Least Mean Square Algorithms
... Least-Mean Square behavior for cyclostationary inputs examined only its convergence in the ...Least Mean Fourth (LMF) algorithm behavior for non-stationary inputs has been recently ...
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Stochastic Approximation Method for Fixed Point Problems
... We study iterative processes of stochastic approximation for finding fixed points of weakly contractive and nonexpan- sive operators in Hilbert spaces under the condition that operators are given with random errors. We ...
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ABSTRACT : Adaptive filter algorithm is a widely used method in communication systems, control systems, digital
... overall convergence process also influences the adaptive ...Least Square (RLS) ,Least Mean Square (LMS), Normalized Least Mean Square (NLMS) and Leaky Least Mean ...
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A Review on Application of Adaptive Algorithms in Signal Processing
... faster convergence NLMS is modified and simulation results show the high quality of Noise Cancelation and minimized mean square ...that convergence rate of modified NLMS is faster than NLMS ...
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Almost convergence and generalized weighted mean II
... In this paper, we investigate some new sequence spaces, which naturally emerge from the concepts of almost convergence and generalized weighted mean. The object of this paper is to introduce the new ...
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Convergence of iterates of pre-mean-type mappings
... geometric mean. Similar convergence, in a neighborhood of the diagonal, occurs also in the case when t = 2s − 1 (Theorem ...than mean-type mappings, the iterates of the pre-mean-type mappings ...
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Mean Square Cordial Labeling of Some Snake Graphs
... admits mean square cordial labeling. In particular , mean square cordial labeling of a Triangular snake Tk, Subdivision of a triangular snake S(Tk), Quadrilateral snake QSk, Subdivision of a ...
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Random Crank Nicolson Scheme for Random Heat Equation in Mean Square Sense
... The random heat equation can be solved numerically by using mean square convergent Crank-Nicolson scheme. The random variable in the Crank-Nicolson scheme is must second order random variable and the random ...
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