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Simple and effective complementary label learning based on mean square error loss
A complementary label specifies one of the classes that an instance does not belong to. Complementary label learning only uses training instances...
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Nonlinear Multiple-Delay Feedback Based Kernel Least Mean Square Algorithm
In this paper, a novel algorithm called nonlinear multiple-delay feedback kernel least mean square (NMDF-KLMS) is proposed by introducing a nonlinear...
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Generative adversarial network (GAN) and enhanced root mean square error (ERMSE): deep learning for stock price movement prediction
The prediction of stock price movement direction is significant in financial circles and academic. Stock price contains complex, incomplete, and...
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A novel quantum calculus-based complex least mean square algorithm (q-CLMS)
The Least Mean Square (LMS) algorithm has a slow convergence rate as it is dependent on the eigenvalue spread of the input correlation matrix. In...
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Zero root-mean-square error for single- and double-diode photovoltaic models parameter determination
The parameter determination based on experimental data aids in providing an accurate assessment for predicting the output current of the PV cells....
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Shear complex modulus imaging utilizing frequency combination in the least mean square/algebraic Helmholtz inversion
Complex shear modulus imaging (CSMI) is a technique used to determine the elasticity and viscosity of soft tissues; it aids in investigating tissue...
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Generalized complex kernel least-mean-square algorithm with adaptive kernel widths
A novel variable kernel width generalized complex-valued least mean-square (VKW-GCKLMS) algorithm aims to optimize kernel width in online way to...
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Speech Dereverberation Based on Scale-Aware Mean Square Error Loss
Recently, deep learning-based speech dereverberation appro-aches have achieved remarkable performance by directly map** the input spectrogram to a...
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Geometric algebra based least-mean absolute third and least-mean mixed third-fourth adaptive filtering algorithms
With regards to the problem of multidimensional signal processing in the field of adaptive filtering, geometric algebra based higher-order statistics...
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Robust maximum correntropy criterion based square-root rotating lattice Kalman filter
Lattice Kalman filter (LKF) is a nonlinear Kalman filter that utilizes a deterministic sampling method with the advantages of optional sampling...
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An Enhanced Extreme Learning Machine Based on Square-Root Lasso Method
Extreme learning machine (ELM) is one of the most notable machine learning algorithms with many advantages, especially its training speed. However,...
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Analyzing the performance of geometric mean optimization-based artificial neural networks for cryptocurrency forecasting
In this study, we utilize a recently proposed non-parametric metaheuristic algorithm known as geometric mean optimization (GMO) to adjust the hidden...
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Error-free and mean value based reversible data hiding using gravitational search algorithm in encrypted images
In recent years the data hiding on encrypted image is significant topic for data security. Due to its capability for preserving confidentiality,...
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Comparison of Root Mean Square Index and Hilbert-Huang Transform for Detection of Muscle Activation in a Person with Elbow Disarticulation
An active prosthesis is a device developed to substitute an absent limb of the human body supplying its functionalities without neglecting the...
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Improved cross sample entropy with error-metric based cardiac variability time series evaluation
The cardiac rate variability analysis is a tool used to diagnose pathological and physiological variations in subjects in the premature stages. The...
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Square Root and Inverse Square Root
Adaptive computation of the square root and inverse square root of the real-time correlation matrix of a streaming sequence {xk∈ℜn} has numerous...
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OptiSembleForecasting: optimization-based ensemble forecasting using MCS algorithm and PCA-based error index
Ensemble forecasts from multiple models have gained enormous popularity as it provides a more efficient forecast as compared to the individual...
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Error Handling
Chapter 5 discusses how SYCL extends C++ to manage error handling when using accelerators. Understanding the difference between synchronous and...
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Steady-state analysis of diffusion least-mean squares with deficient length over wireless sensor networks
In recent years, distributed adaptive processing has received much attention from both theoretical and practical aspects. One of the efficient...
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Convolutional Neural Network Prediction Error Algorithm Based on Block Classification Enhanced
Reversible data hiding techniques can effectively solve the information security problem, and One crucial approach to enhance the level of reversible...