convolution

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convolution

 [kon″vo-lu´shun]
a tortuous irregularity or elevation caused by the infolding of a structure upon itself.

con·vo·lu·tion

(kon'vō-lū'shŭn),
1. A coiling or rolling of an organ.
2. Specifically, a gyrus of the cerebral cotex or folia of the cerebellar cortex.
[L. convolutio]

convolution

(kŏn′və-lo͞o′shən)
n.
1. A form or part that is folded or coiled.
2. One of the convex folds of the surface of the brain.

con′vo·lu′tion·al adj.

convolution

(1) A redundancy or folding of tissue native to an organ. 
(2) Gyrus, brain.

convolution

An elevation on the surface of a structure and an infolding of the tissue upon itself

con·vo·lu·tion

(kon-vŏ-lū'shŭn)
1. A coiling or rolling of an organ.
2. Specifically, a gyrus of the cerebral or cerebellar cortex.
[L. convolutio]
References in periodicals archive ?
Nonlinear Grey Modelling with Convolution Integral: NGMC (1,n).
Tien, "The deterministic grey dynamic model with convolution integral DGDMC(1,n)" Applied Mathematical Modelling, vol.
Cavicchi, Simplified method for analytical evaluation of convolution integrals, IEEE Trans.
Double convolution integral equations involving the general polynomials, Ganita Sandesh, 4(2): 99-103.
Buschman, Theory and Applications of Convolution Integral Equations, Kluwer Academic Publishers, Dordrecht, Boston, London.
Raina, A class of convolution integral equations, J.
In contrast with CWR-BUCKLE program, which use probability density functions, the probabilistic computational algorithm of SCFJ program is based on the evaluation of convolution integrals (Ghiocel & Lungu, 1975) in a discrete approach (Ghiocel & Lungu, 1982), using the histograms of the main parameters which characterize the stability of the CWR track (Ungureanu & Dosa, 2007).
In a similar way, the other two convolution integrals in Equation (14) can be expressed as
Convergence in variation and rates of approximation for Bernstein-type polynomials and singular convolution integrals. Analysis (Munich), 2003, 23, 299-340.
A state-space description of a LTI-TDS can be provided by the set of FDEs in the form (1) where x [member of][[??].sup.n] is a vector of state variables, u [member of] [[??].sup.m] stands for a vector of inputs, y [member of] [[??].sup.l] represents a vector of outputs, [A.sub.i], A([tau]), [B.sub.i], B([tau]), C, [H.sub.i] are real matrices of compatible dimensions, sums with 0 [less than or equal to] [[eta].sub.i] [less than or equal to] L stand for lumped (point-wise) delays and convolution integrals express distributed delays.
We will restrict our attention to convolution integrals throughout the remainder of this paper.
Later, the often ray-tube integration called approach was employed for 2D ISAR image generation [8] and it was even recognized that the resulting convolution integrals can be efficiently evaluated by Fast Fourier Transform (FFT) based fast convolutions [9].