stochastic gradient adaptive filter algorithm
Acoustic Echo Cancellation by Adaptive Combination of Normalized Sub band Adaptive Filters by Using Stochastic Gradient Algorithm
... communication. Adaptive filtering techniques are used to reduce this unwanted echo thus increasing communication ...the adaptive filter is highly correlated and the impulse response of the echo path ...
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Quaternion Information Theoretic Learning Adaptive Algorithms for Nonlinear Adaptive
... QKSIG algorithm minimizes Shannon’s entropy of the error between the filter output and desired response and minimizes the divergence between the joint densities of input-desired and input-output ...
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On an Adaptive Filter based on Simultaneous Perturbation Stochastic Approximation Method
... SPSA algorithm is very simple to implement since it requires only two integrations of direct numerical model for estimating the gradient of objective ...the gradient by linearization ...
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ELIMINATION OF HIGH DENSITY IMPULSE NOISE USING DISTANCE BASED ADAPTIVE MEAN FILTER ALGORITHM
... based adaptive mean filter method for the re-establishment of gray-scale images that are highly corrupted by impulse noise, is proposed in this paper ...a filter is used to identify some of the ...
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Minimum Bit Error Rate Design for Space Time Equalisation Based Multiuser Detection
... (BER). Adaptive implementations of the MBER STE are considered, and both the block-data-based and sample-by-sample adaptive MBER algorithms are ...(LBER) algorithm, is compared with the most popular ...
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Certain Systems Arising In Stochastic Gradient Descent
... Here, we will discuss the ODE-method for a more detailed exposition, see [KY03], which is used to establish convergence results for stochastic approximations. This method links the asymptotic behavior of the ...
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An information theoretic approach to speech feature selection applied to speech detection
... Computation of this information metric for speech training sets has shown the first adaptive linear prediction coefficient from the stochastic gradient algorithm to be the optimal single[r] ...
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Stochastic Optimization for Big Data Analytics: Algorithms and Libraries
... Stochastic Gradient Descent (Pegasos) for L1-SVM (primal) Stochastic Dual Coordinate Ascent (SDCA) for L2-SVM (dual) Stochastic Average Gradient (SAG) for Logistic Regression/Regression?[r] ...
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Parameter Identification of Nonlinear Systems with Time delay Based on the Multi innovation Stochastic Gradient Algorithm
... Abstract This paper considers the parameter identification problem of block-oriented Hammerstein nonlinear systems with time-delay. Firstly, we adopt the data filtering technique to transform the identification model so ...
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arxiv: v1 [cs.lg] 10 Jun 2013
... for stochastic optimization the use of smoothness only leads to improvements on constants ...tic gradient descent with constant step-size achieves the desired ...novel stochastic gradient ...
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An Unsupervisory Qualitative Image Enhancement using Adaptive Morphological Bilateral Filter for Medical Images
... the adaptive bilateral filter (ABF) is shown better performance than the ordinary form of the bilateral ...This filter is modified with two important ...range filter. Next both width and range ...
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Removal of High Density Salt and Peppers Noise and Edge Preservation in Color Image Through Trimmed Mean Adaptive Switching Bilateral Filter
... Noise is the most annoying problem [6] in image processing. One method to get rid of this difficulty is the development of such a robust algorithm that can perform the dealing out tasks in presence of noise. The ...
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A Service System with On-Demand Agents, Stochastic Gradient Algorithms and the SARAH Algorithm
... Figure 4.5 shows numerical results in terms of loss residuals (top) and test errors (bot- tom) on the four datasets, SARAH is sometimes comparable or a little worse than other methods at the beginning. However, it ...
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Enhanced genetic algorithm-based back propagation neural network to diagnose conditions of multiple-bearing system
... The random initial connectivity weights can induce unsatisfactory of condition diagnosis accuracy from standard BPNN (Chang et al., 2012). The randomness of initial connectivity weights can be minimized by setting up ...
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An active noise control algorithm with gain and power constraints on the adaptive filter
... gain-constrained adaptive systems in- clude systems that use a microphone for feedback, and due to the acoustic path to the microphone notches or peaks occur in the microphone frequency response (which may not be ...
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A Simulation-Based Algorithm for Ergodic Control of Markov Chains Conditioned on Rare Events
... an algorithm for long-run average cost MDPs is ...cost gradient is approximated using that associated with a corresponding infinite horizon discounted cost MDP ...the algorithm in Baxter and Bartlett ...
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Time series modeling and filtering method of electric power load stochastic noise
... The first stationarity test results of power load data is as following: ∣u∣ = 2.54 > 1.96, which means it doesn’t meet the stationarity requirement. After extracting trend, the result is this, namely ∣u∣ = 0.5 < ...
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Development of Smart Number Writing Robotic Arm using Stochastic Gradient Decent Algorithm
... The Graphical User Interface (GUI) code has been written using PtCharm software, which is IDE that is developed for Python language. As well the layout design of GUI shown in Fig. 5 has been created in software Qt ...
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A Scale Adaptive Method Based On Quaternion Correlation in Object Tracking
... In the video sequences, the women's size changed from small to large. It was shown that when the women's size did not change too much, both of the two algorithms could get accuracy results. When the women came closer, ...
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Removal of Power Line Noise from EMG Signals Using Rls Algorithm
... RLS algorithm to remove the artifacts from EMG. This algorithm enjoys less computational complexity and good filtering ...machine algorithm called BPNN (Back propagation neural network) is used and ...
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