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Integral expressing the amount of overlap of one function as it is shifted over another
In mathematics (in particular, functional analysis), convolution is a mathematical operation on two functions f {\displaystyle f} and g {\displaystyle
Convolution
Theorem in mathematics
In mathematics, the convolution theorem states that under suitable conditions the Fourier transform of a convolution of two functions (or signals) is the
Convolution_theorem
Type of feedforward neural network
A convolutional neural network (CNN) is a type of feedforward neural network that learns features via filter (or kernel) optimization. This type of deep
Convolutional_neural_network
Mathematical operation
Circular convolution, also known as cyclic convolution, is a special case of periodic convolution, which is the convolution of two periodic functions that
Circular_convolution
Mathematical operation on arithmetical functions
In mathematics, Dirichlet convolution (or divisor convolution) is a binary operation defined for arithmetic functions; it is important in number theory
Dirichlet_convolution
Topics referred to by the same term
mathematics, convolution is a binary operation on functions. Circular convolution Convolution theorem Titchmarsh convolution theorem Dirichlet convolution Infimal
Convolution_(disambiguation)
Neural network technology
neural networks, a convolutional layer is a type of network layer that applies a convolution operation to the input. Convolutional layers are some of
Convolutional_layer
Mathematical operation in signal processing
discrete convolution is the discrete analog of the multidimensional convolution of functions on Euclidean space. It is also a special case of convolution on
Multidimensional discrete convolution
Multidimensional_discrete_convolution
Algorithm to smooth data points
distorting the signal tendency. This is achieved, in a process known as convolution, by fitting successive sub-sets of adjacent data points with a low-degree
Savitzky–Golay_filter
Mathematical inequality about the convolution of two functions
In mathematics, Young's convolution inequality is a mathematical inequality about the convolution of two functions, named after William Henry Young. In
Young's convolution inequality
Young's_convolution_inequality
Probability distribution of the sum of random variables
The convolution/sum of probability distributions arises in probability theory and statistics as the operation in terms of probability distributions that
Convolution of probability distributions
Convolution_of_probability_distributions
Matrix used in image processing to alter an image
In image processing, a kernel, convolution matrix, or mask is a small matrix used for blurring, sharpening, embossing, edge detection, and more. This
Kernel_(image_processing)
scale convolution of two functions s ( t ) {\displaystyle s(t)} and r ( t ) {\displaystyle r(t)} , also known as their logarithmic convolution or log-volution
Logarithmic_convolution
Function in discrete mathematics
partial differential equations, and to perform other operations such as convolutions or multiplying large integers. Since the DFT deals with a finite amount
Discrete_Fourier_transform
Type of error-correcting code using convolution
represents the 'convolution' of the encoder over the data, which gives rise to the term 'convolutional coding'. The sliding nature of the convolutional codes facilitates
Convolutional_code
Mathematical concept
space of convolution quotients is a field of fractions of a convolution ring of functions: a convolution quotient is to the operation of convolution as a
Convolution_quotient
The Titchmarsh convolution theorem describes the properties of the support of the convolution of two functions. It was proven by Edward Charles Titchmarsh
Titchmarsh convolution theorem
Titchmarsh_convolution_theorem
Free convolution is the free probability analog of the classical notion of convolution of probability measures. Due to the non-commutative nature of free
Free_convolution
Artificial reverberation effect
electromechanical transducers to create vibrations in large plates of sheet metal. Convolution reverb uses impulse responses to record the reverberation of physical
Reverb_effect
convolution is a special subset of convolution operations in which the convolution kernel is symmetric across its zero point. Many common convolution-based
Symmetric_convolution
Convolution
category theory, Day convolution is an operation on functors that can be seen as a categorified version of function convolution. It was first introduced
Day_convolution
Extension of cubic spline interpolation
accomplished using either Lagrange polynomials, cubic splines, or cubic convolution algorithm. In image processing, bicubic interpolation is often chosen
Bicubic_interpolation
Mathematical concept
In mathematics, the convolution power is the n-fold iteration of the convolution with itself. Thus if x {\displaystyle x} is a function on Euclidean space
Convolution_power
Method for visualizing vector fields
In scientific visualization, line integral convolution (LIC) is a method to visualize a vector field (such as fluid motion) at high spatial resolutions
Line_integral_convolution
negacyclic convolution is a convolution between two vectors a and b. It is also called skew circular convolution or wrapped convolution. It results from
Negacyclic_convolution
Topics referred to by the same term
products, bounding the product of two quantities Young's convolution inequality, bounding the convolution product of two functions Young's inequality for integral
Young's_inequality
Family of computer vision models designed for efficient inference on mobile devices
MobileNet is a family of convolutional neural network (CNN) architectures designed for image classification, object detection, and other computer vision
MobileNet
Gyrus of the primary auditory cortex of the brain
temporal gyrus, also called Heschl's gyrus (/ˈhɛʃəlz ˈdʒaɪrəs/) or Heschl's convolutions, is a gyrus found in the area of each primary auditory cortex buried
Transverse_temporal_gyrus
Decodes a bitstream with the Viterbi algorithm
that has been encoded using a convolutional code or trellis code. There are other algorithms for decoding a convolutionally encoded stream (for example
Viterbi_decoder
section of the beam. However, convolution can be used in certain cases to improve computational efficiency. In order for convolution to be used to calculate
Convolution for optical broad-beam responses in scattering media
Convolution_for_optical_broad-beam_responses_in_scattering_media
Type of artificial neural network
consists of three sequential convolutional layers and a residual connection. The first layer in this block is a 1×1 convolution for dimension reduction (e
Residual_neural_network
Discrete Fourier transform for prime sizes
a cyclic convolution (the other algorithm for FFTs of prime sizes, Bluestein's algorithm, also works by rewriting the DFT as a convolution). Since Rader's
Rader's_FFT_algorithm
science, a convolutional deep belief network (CDBN) is a type of deep artificial neural network composed of multiple layers of convolutional restricted
Convolutional deep belief network
Convolutional_deep_belief_network
Method in signal processing
is the traditional name for an efficient way to evaluate the discrete convolution between a very long signal x [ n ] {\displaystyle x[n]} and a finite
Overlap–save_method
Integral transform and linear operator
The Hilbert transform is given by the Cauchy principal value of the convolution with the function 1 / ( π t ) {\displaystyle 1/(\pi t)} (see § Definition)
Hilbert_transform
Class of artificial neural networks
implement different flavors of message passing, started by recursive or convolutional constructive approaches. A 2022 position paper argued that many architectures
Graph_neural_network
Series of convolutional neural networks for image classification
The VGGNets are a series of convolutional neural networks (CNNs) developed by the Visual Geometry Group (VGG) at the University of Oxford. The VGG family
VGGNet
distribution of the sum of two or more independent random variables is the convolution of their individual distributions. The term is motivated by the fact
List of convolutions of probability distributions
List_of_convolutions_of_probability_distributions
Method in signal processing
the overlap–add method is an efficient way to evaluate the discrete convolution of a very long signal x [ n ] {\displaystyle x[n]} with a finite impulse
Overlap–add_method
Mathematical transform
of graph structured learning algorithms, such as the widely employed convolutional networks. Given an undirected weighted graph G = ( V , E ) {\displaystyle
Graph_Fourier_transform
Transformation of a mathematical sequence
under the binomial convolution. There is also another binomial convolution in the mathematical literature. The binomial convolution of arithmetical functions
Binomial_transform
Family of convolutional neural networks
Inception is a family of convolutional neural network (CNN) for computer vision, introduced by researchers at Google in 2014 as GoogLeNet (later renamed
Inception (deep learning architecture)
Inception_(deep_learning_architecture)
Mathematical model which is both linear and time-invariant
found directly using convolution: y(t) = (x ∗ h)(t) where h(t) is called the system's impulse response and ∗ represents convolution (not to be confused
Linear_time-invariant_system
Convolutional neural network structure
LeNet is a series of convolutional neural network architectures created by a research group at AT&T Bell Laboratories between of the period of 1988 to
LeNet
Response if an optical system to a point source of light
everywhere in the imaging space, the image of a complex object is then the convolution of that object and the PSF. The PSF can be derived from diffraction integrals
Point_spread_function
Neurological factors responsible for intelligence
[dubious – discuss] The folding of the brain's surface, known as cortical convolution, has become more pronounced throughout human evolution. It has been suggested
Neuroscience_and_intelligence
Device for suppressing part of a signal
the behavior of the filter as a convolution of the time-domain input with the filter's impulse response. The convolution theorem, which holds for Laplace
Filter_(signal_processing)
Directional cubic convolution interpolation (DCCI) is an edge-directed image scaling algorithm created by Dengwen Zhou and Xiaoliu Shen. By taking into
Directional cubic convolution interpolation
Directional_cubic_convolution_interpolation
Branch of machine learning
connected networks, deep belief networks, recurrent neural networks, convolutional neural networks, generative adversarial networks, transformers, and
Deep_learning
Reconstruction of a filtered signal
In mathematics, deconvolution is the inverse of convolution. Both operations are used in signal processing and image processing. For example, it may be
Deconvolution
Function whose graph is 0, then 1, then 0 again, in an almost-everywhere continuous way
{\sin(\pi af)}{\pi af}}=a\ \operatorname {sinc} _{\pi }{(af)}.} The self convolution of the dis-continuous rectangular function results in the triangular
Rectangular_function
Objects that generalize functions
possible to define the convolution of a function with a distribution, or even the convolution of two distributions. Convolution of a test function with
Distribution (mathematical analysis)
Distribution_(mathematical_analysis)
Generalization of the Legendre transformation
functions. The infimal convolution of two functions has a geometric interpretation: The (strict) epigraph of the infimal convolution of two functions is
Convex_conjugate
Mathematical theorem on convolved binomial coefficients
In combinatorics, Vandermonde's identity (or Vandermonde's convolution) is the following identity for binomial coefficients: ( m + n r ) = ∑ k = 0 r (
Vandermonde's_identity
Influential 2012 deep convolutional neural network
AlexNet is a convolutional neural network architecture developed for image classification tasks, notably achieving prominence through its performance
AlexNet
Integration kernels for smoothing out sharp features
smooth functions approximating nonsmooth (generalized) functions, via convolution. Intuitively, given a (generalized) function, convolving it with a mollifier
Mollifier
Concept in machine learning
parameter space. From 2014 to 2015, tensor methods become more common in convolutional neural networks (CNNs). Tensor methods organize neural network weights
Tensor_(machine_learning)
Mathematical form
\mathrm {d} \tau } is well defined and is called the convolution. Under the Fourier transform, convolution becomes point-wise function multiplication. The
Product_(mathematics)
Type of parallel computing architecture of tightly coupled nodes
convolution. Similarly, n-dimensional convolution can be computed by an n-dimensional array of PEs. Many other implementations of the 1D convolutions
Systolic_array
Fitting an approximating function to data
a matrix transformation is called convolution. Thus the matrix is also called convolution matrix or a convolution kernel. In the case of simple series
Smoothing
Deep learning model structure
multilayer perceptron networks, these layers are stacked together. The Convolutional layer is typically used for image analysis tasks. In this layer, the
Layer_(deep_learning)
Mathematical algorithm
obtain the convolution of a and b, according to the usual convolution theorem. Let us also be more precise about what type of convolution is required
Chirp_Z-transform
Image-generating machine learning model
models. The "zero convolution" is a 1×1 convolution with both weight and bias initialized to zero. Before training, all zero convolutions produce zero output
Stable_Diffusion
In statistics, the Hájek–Le Cam convolution theorem states that any regular estimator in a parametric model is asymptotically equivalent to a sum of two
Hájek–Le Cam convolution theorem
Hájek–Le_Cam_convolution_theorem
Computational model used in machine learning
units (GPUs), and large datasets. Architectural innovations such as convolutional neural networks (CNNs) significantly improved performance in computer
Neural network (machine learning)
Neural_network_(machine_learning)
Function which maps a tuple of sequences into a sequence of tuples
In computer science, zipping is a function which maps a tuple of sequences into a sequence of tuples. This name zip derives from the action of a zipper
Zipping_(computer_science)
Problem in computational complexity theory
the set S + S {\displaystyle S+S} of all pairwise sums as a discrete convolution using the fast Fourier transform, and finally comparing this set to S
3SUM
2017 research paper by Google
generate the output. Since the Transformer does not rely on recurrence or convolution of the text in order to perform encoding and decoding, the paper relied
Attention_Is_All_You_Need
Computer scientist (born 1986)
With Alex Krizhevsky and Geoffrey Hinton, he co-created AlexNet, a convolutional neural network. One of the most highly cited computer scientists in
Ilya_Sutskever
Fourier analysis technique applied to sequences
} The significance of this result is explained at circular convolution and fast convolution algorithms. S 2 π ( ω ) {\displaystyle S_{2\pi }(\omega )}
Discrete-time Fourier transform
Discrete-time_Fourier_transform
Rational mathematical function indexed by integer partitions
In mathematics, Weingarten functions are rational functions indexed by partitions of integers that can be used to calculate integrals of products of matrix
Weingarten_function
Distance function defined between probability distributions
y ) {\displaystyle f(x)=\inf _{y}d(x,y)-g(y)} , making it an infimal convolution of − g {\displaystyle -g} with a cone. This implies f ( x ) − f ( y )
Wasserstein_metric
Topological algebra associated to continuous groups
measure μ called a Haar measure. Using the Haar measure, one can define a convolution operation on the space Cc(G) of complex-valued continuous functions on
Group algebra of a locally compact group
Group_algebra_of_a_locally_compact_group
distributions says that every probability distribution P admits (in the convolution semi-group of probability distributions) a factorization P = P 1 ⊗ P
Khinchin's theorem on the factorization of distributions
Khinchin's_theorem_on_the_factorization_of_distributions
Functions in harmonic analysis mathematics
1)} estimates. A singular integral of convolution type is an operator T {\displaystyle T} defined by convolution with a kernel K {\displaystyle K} that
Singular_integral
Concept in mathematics
specifically in mathematical analysis, the Cauchy product is the discrete convolution of two infinite series. It is named after the French mathematician Augustin-Louis
Cauchy_product
Polish mathematician
is based upon an algebra of the convolution of functions with respect to the Fourier transform. From the convolution product he goes on to define what
Jan_Mikusiński
Type of machine learning model
Yanming (2021). "Review of Image Classification Algorithms Based on Convolutional Neural Networks". Remote Sensing. 13 (22): 4712. Bibcode:2021RemS..
Large_language_model
Covariance and correlation
and neurophysiology. The cross-correlation is similar in nature to the convolution of two functions. In an autocorrelation, which is the cross-correlation
Cross-correlation
Filter in electronics and signal processing
systems. Mathematically, a Gaussian filter modifies the input signal by convolution with a Gaussian function; this transformation is also known as the Weierstrass
Gaussian_filter
of the symbol so the linear convolution of a frequency-selective multipath channel can be modeled as circular convolution, which in turn may transform
Cyclic_prefix
Probability distribution
(named after Woldemar Voigt) is a probability distribution given by a convolution of a Cauchy-Lorentz distribution and a Gaussian distribution. It is often
Voigt_profile
Concept in the solution of linear partial differential equations
the most important case, directly linked to the possibility of using convolution to solve an arbitrary right hand side — was shown by Bernard Malgrange
Fundamental_solution
Type of convolutional neural network
U-Net is a convolutional neural network that was developed for image segmentation. The network is based on a fully convolutional neural network whose
U-Net
Generating high-resolution video frames from given low-resolution ones
frame sequence, k {\displaystyle k} — blur kernel, ∗ {\displaystyle *} — convolution operation, ↓ s {\displaystyle \downarrow {_{s}}} — downscaling operation
Video_super-resolution
Aspect of probability theory
distribution. Addition of random variables, on the other hand, are the convolution of their probability distributions. Let X and Y be independent random
Sum of normally distributed random variables
Sum_of_normally_distributed_random_variables
Massacres of Poles by Ukrainian nationalists during World War II
history. University of Alberta. 28 March 2011. p. 4, reproduced in The Convolutions of Historical Politics, edited by Alexei Miller and Maria Lipman, 211–238
Massacres of Poles in Volhynia and Eastern Galicia
Massacres_of_Poles_in_Volhynia_and_Eastern_Galicia
known for its simplicity and use of 3x3 convolution filters Inception — CNN architecture using parallel convolutional layers of different sizes LAION OpenAssistant
Lists of open-source artificial intelligence software
Lists_of_open-source_artificial_intelligence_software
AI that generates content
(GPT) series developed by OpenAI, replacing traditional recurrent and convolutional models. The self-attention mechanism enables the model to determine
Generative_AI
Signal (re-)construction algorithm
theorem article, which points out that it can also be expressed as the convolution of an infinite impulse train with a sinc function: x ( t ) = ( ∑ n =
Whittaker–Shannon interpolation formula
Whittaker–Shannon_interpolation_formula
Multilingual neural machine translation service
new languages, with the release of a new implementation that utilizes convolutional neural networks, and also enhanced the speed and quality of Conversation
Google_Translate
Serial concatenated convolutional codes (SCCC) are a class of forward error correction (FEC) codes highly suitable for turbo (iterative) decoding. Data
Serial concatenated convolutional codes
Serial_concatenated_convolutional_codes
French computer scientist (born 1960)
his work on optical character recognition and computer vision using convolutional neural networks (CNNs). He is also one of the main creators of the DjVu
Yann_LeCun
Family of computer vision models
EfficientNet is a family of convolutional neural networks (CNNs) for computer vision published by researchers at Google AI in 2019. Its key innovation
EfficientNet
"Smoothing" integral transform
}}}\int _{-\infty }^{\infty }f(x-y)\;e^{-{\frac {y^{2}}{4}}}\;dy~,} the convolution of f {\displaystyle f} with the Gaussian function 1 4 π e − x 2 / 4
Weierstrass_transform
Mathematical analysis of frequency content of signals
methods. The DFT can also be used to perform other operations such as convolutions or multiplying large integers. The DFT and DCT have seen wide usage across
Multidimensional_transform
estimation and convolution), and Filtering (again in two senses: estimation and convolution). Smoothing (estimation) and smoothing (convolution), despite being
Smoothing problem (stochastic processes)
Smoothing_problem_(stochastic_processes)
Formal power series
transformations Knuth's article titled "Convolution Polynomials" defines a generalized class of convolution polynomial sequences by their special generating
Generating_function
Family of functions in mathematics
{\displaystyle F_{n}(x)\geq 0} with average value of 1 {\displaystyle 1} . The convolution F n {\displaystyle F_{n}} is positive: for f ≥ 0 {\displaystyle f\geq
Fejér_kernel
Neural network coding model
The convolutional sparse coding paradigm is an extension of the global sparse coding model, in which a redundant dictionary is modeled as a concatenation
Convolutional_sparse_coding
CONVOLUTION
CONVOLUTION
CONVOLUTION
CONVOLUTION
Girl/Female
American, Australian, French, German, Hebrew, Latin, Spanish, Swedish
Life; Spanish Form of Eve; To Live; Living One; Animal
Girl/Female
Muslim
Limitless, Protector, Defendant, Central
Male
German
Modern form of Old High German Hrodwulf, RUDOLF means "famous wolf."
Boy/Male
Hindu
Devotee
Boy/Male
English
Foreigner.
Boy/Male
Hindu, Indian
Belonging to the Sun
Boy/Male
Indian
Month of january
Girl/Female
Hindu, Indian, Tamil
Wealth
Girl/Female
Hindu
Myrtle
Boy/Male
Hindu
CONVOLUTION
CONVOLUTION
CONVOLUTION
CONVOLUTION
CONVOLUTION
n.
The act of twisting; a contortion; a flexure; a convolution; a bending.
n. pl.
A general name for all those placental mammals that have a brain with few or no cerebral convolutions, as Rodentia, Insectivora, etc.
n.
A nonplane curve whose tangents are all equally inclined to a given plane. The common helix is the curve formed by the thread of the ordinary screw. It is distinguished from the spiral, all the convolutions of which are in the plane.
n.
A twist; a convolution.
n.
The state of being intervolved or coiled up; a convolution; as, the intervolutions of a snake.
n.
A convoluted ridge between grooves; a convolution; as, the gyri of the brain; the gyri of brain coral. See Brain.
n.
A sinuous depression or sulcus like those separating the convolutions of the brain.
a.
Consisting of many folds, coils, or convolutions.
v. t.
To unite by winding one thread, strand, or other flexible substance, round another; to form by convolution, or winding separate things round each other; as, to twist yarn or thread.
a.
Pertaining to a gyrus, or convolution.
n.
A band of gray matter bordering the fimbria in the brain; the dentate convolution.
n.
The act of rolling anything upon itself, or one thing upon another; a winding motion.
n.
An oblong vermiform mass on the dorsal side of the testicle, composed of numerous convolutions of the excretory duct of that organ.
n.
The state of being rolled upon itself, or rolled or doubled together; a tortuous or sinuous winding or fold, as of something rolled or folded upon itself.
n.
Anything of a rounded or swelling form resembling a roll; a turn; a convolution; a coil.
a.
Having convolutions.
a.
Below the margin; submarginal; as, an inframarginal convolution of the brain.
v. t.
To turn completely, or with repeated turns; especially, to turn about something fixed; to cause to form convolutions about anything; to coil; to twine; to twist; to wreathe; as, to wind thread on a spool or into a ball.
n.
An irregular, tortuous folding of an organ or part; as, the convolutions of the intestines; the cerebral convolutions. See Brain.
n.
A twist; a convolution.