Results 221 to 230 of about 67,963 (266)

A multiple filter-wrapper feature selection algorithm based on process optimization mechanism for high-dimensional omics data analysis. [PDF]

PLoS One
Shi Y, Zheng Y, Bai X.
europepmc   +1 more source

Scalable Distributed Memory Implementation of the Quasi-Adiabatic Propagator Path Integral. [PDF]

J Chem Theory Comput
Ovcharenko R, Xu X, Fingerhut BP.
europepmc   +1 more source

Multi-strategy embedded framework for neoantigen vaccine maturation. [PDF]

Sci Rep
Zhang G, Fu Y, Chan KC, Jin R, Yang Y, Fu L, Zhou R.   +6 more
europepmc   +1 more source

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Convergence index filter for vector fields

IEEE Transactions on Image Processing, 1999
This paper proposes a unique fitter called an iris filter, which evaluates the degree of convergence of the gradient vectors within its region of support toward a pixel of interest. The degree of convergence is related to the distribution of the directions of the gradient vectors and not to their magnitudes.
H Kobatake
exaly   +3 more sources

Convergence of an adaptive filter with signed filtered error

IEEE Transactions on Signal Processing, 1994
The need for high-speed adaptive filters has prompted the search for alternatives to the popular LMS algorithm. One modification is the replacement of the prediction error term in the LMS update kernel by its signum function. At the same time, in noise and echo cancellation problems, reduced residual noise variance often requires error filtering.
Soura Dasgupta, Jeffery S. Garnett, C. Richard Johnson Jr.   +2 more
openaire   +1 more source

On the convergence of Bayesian adaptive filtering

Proceedings of the Eighth International Symposium on Signal Processing and Its Applications, 2005., 2006
Standard adaptive filtering algorithms, including the popular LMS and RLS algorithms, possess only one parameter (stepsize, forgetting factor) to adjust the tracking speed in a nonstationary environment. Furthermore, existing techniques for the automatic adjustment of this parameter are not totally satisfactory and are rarely used.
Tayeb Sadiki, Dirk T. M. Slock
openaire   +1 more source

Convergent algorithms for collaborative filtering

Proceedings of the 4th ACM conference on Electronic commerce, 2003
A collaborative filtering system analyzes data on the past behavior of its users so as to make recommendations --- a canonical example is the recommending of books based on prior purchases. The full potential of collaborative filtering implicitly rests on the premise that, as an increasing amount of data is collected, it should be possible to make ...
Jon M. Kleinberg, Mark Sandler 0002
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Convergence behavior and convergence rates of stack filters

1991 IEEE International Symposium on Circuits and Systems (ISCAS), 1991
The convergence behavior of type-0 through type-3 stack filters is investigated. It is shown that stack filters of type-0 through type-2 all possess the convergence property; that is, they filter any input signal to a root after consecutive passes of the filter under any appending strategy.
M. Gabbouj, P.-T. Yu, E.J. Coyle
openaire   +1 more source