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Wave packet transform and wavelet convolution product involving the index Whittaker transform
The main goal of this paper is to study the wave packet transform (WPT) and wavelet convolution product involving the index Whittaker transform...
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The Hartley–Bessel function: product formula and convolution structure
This paper explores a one-parameter extension of the Hartley kernel expressed as a real combination of two Bessel functions, termed the...
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Product-Convolution of Heavy-Tailed and Related Distributions
Products of random variables and related distribution problems appear in physics, engineering, number theory, and many probability and statistical...
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Convolution of Distributions
The convolution product plays a central role in the description of linear and weakly-nonlinear systems. In this chapter we develop its theory based...
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Convolution Integral and Sum
The convolution integral of two functions x(t) and h(t) is written x*h and is defined as the integral of the product of the two functions after one...
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Falcon: lightweight and accurate convolution based on depthwise separable convolution
How can we efficiently compress convolutional neural network (CNN) using depthwise separable convolution, while retaining their accuracy on...
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Continuous Time Convolution
Convolution is defined as the integral of the product of two continuous functions that produce a third function of the same variable, e.g., f(t). In...
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Convolution
Convolution and the resulting circulant matrices are fundamental tools used in signal processing and data analysis. It is a natural place for the use...
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High-dimensional graphs convolution for quantum walks photonic applications
Quantum random walks represent a powerful tool for the implementation of various quantum algorithms. We consider a convolution problem for the graphs...
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Convolution Equations
The objective of this chapter is to show that the solution of ordinary differential equations, if based on distributions as opposed to functions, can...
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The Hadamard–Bergman Convolution on the Half-Plane
We introduce the Hadamard–Bergman convolution on the half-plane. We show that it exists in terms of the Hadamard product and it is commutative on the...
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Metric convolution and frames
The fractal convolution of two map**s is a binary operation in some space of functions. In previous papers we extracted the main properties of this...
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Dynamic convolution-based image dehazing network
Convolutional neural networks use a convolutional kernel with static weights for processing non-uniform haze or dense fog, which may lead to...
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Convolution and Duhamel Integrals
The convolution and Duhamel (step response) integrals are reviewed. The Duhamel integral will be used in Chap. 15...
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Group-Covariant Stochastic Products and Phase-Space Convolution Algebras
A quantum stochastic product is defined as a binary operation on the convex set of quantum states that preserves the convex structure. We discuss a...
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Dense-scale dynamic network with filter-varying atrous convolution for semantic segmentation
Deep convolution neural networks (DCNNs) in deep learning have been widely used in semantic segmentation. However, the filters of most regular...
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Inverse and Moore–Penrose inverse of conditional matrices via convolution
Moore–Penrose inverse emerges in statistics, neural networks, machine learning, applied physics, numerical analysis, tensor computations, solving...
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Optimization of optical convolution kernel of optoelectronic hybrid convolution neural network
To enhance the optical computation’s utilization efficiency, we develop an optimization method for optical convolution kernel in the optoelectronic...
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Accelerating Image Processing Using Reduced Precision Calculation Convolution Engines
In this paper a method of accelerating image processing using convolution engines with reduced precision calculation is presented. The convolution...
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Multi-attention gated temporal graph convolution neural Network for traffic flow forecasting
Real-time and accurate traffic flow forecasting plays a crucial role in transportation systems and holds great significance for urban traffic...
