Single photon avalanche diodes (SPADs) fabricated in PureB silicon technology offer exceptional versatility, functioning both as light emitting diodes and detectors sensitive down to a single photon. In PureB technolo...
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Depression is a major public health concern, affecting millions worldwide, and necessitates early, accurate detection for timely intervention. This study focuses on enhancing machine learning (ML) and deep learning (D...
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Augmented Reality (AR) and Virtual Reality (VR) systems involve computationally intensive image processing algorithms that can burden end-devices with limited resources, leading to poor performance in providing low la...
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This paper presents a method to control the out-ofband performance of absorptive filters in both narrowband and wideband cases. To verify the method, a narrowband absorptive filter is designed with wideband matching, ...
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Neural networks have become a leading model in modern machine learning, able to model even the most complex data. For them to be properly trained, however, a lot of computational resources are required. With the carbo...
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Smartphones and tablets (SPT) have become an integral part of daily life, and their added value for biology education was seriously tested during the COVID -19 pandemic in distance education. We collected data from 35...
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Harmonic radar systems are used to interrogate, or track a location of, passive nonlinear targets in highly cluttered environments, and they are notorious for their poor power efficiency and low detection ranges. Due ...
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We investigate the statistical behavior of gradient descent iterates with dropout in the linear regression model. In particular, non-asymptotic bounds for the convergence of expectations and covariance matrices of the...
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We investigate the statistical behavior of gradient descent iterates with dropout in the linear regression model. In particular, non-asymptotic bounds for the convergence of expectations and covariance matrices of the iterates are derived. The results shed more light on the widely cited connection between dropout and ℓ2-regularization in the linear model. We indicate a more subtle relationship, owing to interactions between the gradient descent dynamics and the additional randomness induced by dropout. Further, we study a simplified variant of dropout which does not have a regularizing effect and converges to the least squares estimator.
Due to the fact that a memristor with memory properties is an ideal electronic component for implementation of the artificial neural synaptic function,a brand-new tristable locally active memristor model is first prop...
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Due to the fact that a memristor with memory properties is an ideal electronic component for implementation of the artificial neural synaptic function,a brand-new tristable locally active memristor model is first proposed in this ***,a novel four-dimensional fractional-order memristive cellular neural network(FO-MCNN)model with hidden attractors is constructed to enhance the engineering feasibility of the original CNN model and its ***,its hardware circuit implementation and complicated dynamic properties are investigated on multi-simulation ***,it is used toward secure communication application *** it as the pseudo-random number generator(PRNG),a new privacy image security scheme is designed based on the adaptive sampling rate compressive sensing(ASR-CS)***,the simulation analysis and comparative experiments manifest that the proposed data encryption scheme possesses strong immunity against various security attack models and satisfactory compression performance.
Dynamic multi-objective optimization problems (DMOPs) are common in real-world applications. To effectively address these problems, algorithms are required to maintain solution diversity and quickly adapt to environme...
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