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Ad-hoc On-Demand Distance Vector Routing

by Charles E. Perkins, Elizabeth M. Royer - IN PROCEEDINGS OF THE 2ND IEEE WORKSHOP ON MOBILE COMPUTING SYSTEMS AND APPLICATIONS , 1997
"... An ad-hoc network is the cooperative engagement of a collection of mobile nodes without the required intervention of any centralized access point or existing infrastructure. In this paper we present Ad-hoc On Demand Distance Vector Routing (AODV), a novel algorithm for the operation of such ad-hoc n ..."
Abstract - Cited by 3240 (14 self) - Add to MetaCart
An ad-hoc network is the cooperative engagement of a collection of mobile nodes without the required intervention of any centralized access point or existing infrastructure. In this paper we present Ad-hoc On Demand Distance Vector Routing (AODV), a novel algorithm for the operation of such ad

Highly Dynamic Destination-Sequenced Distance-Vector Routing (DSDV) for Mobile Computers

by Charles E. Perkins, Pravin Bhagwat , 1994
"... An ad-hoc network is the cooperative engagement of a collection of Mobile Hosts without the required intervention of any centralized Access Point. In this paper we present an innovative design for the operation of such ad-hoc networks. The basic idea of the design is to operate each Mobile Host as a ..."
Abstract - Cited by 2076 (8 self) - Add to MetaCart
as a specialized router, which periodically advertises its view of the interconnection topology with other Mobile Hosts within the network. This amounts to a new sort of routing protocol. We have investigated modifications to the basic Bellman-Ford routing mechanisms, as specified by RIP [5], to make

A New Kind of Science

by Stephen Wolfram , 2002
"... “Somebody says, ‘You know, you people always say that space is continuous. How do you know when you get to a small enough dimension that there really are enough points in between, that it isn’t just a lot of dots separated by little distances? ’ Or they say, ‘You know those quantum mechanical amplit ..."
Abstract - Cited by 893 (0 self) - Add to MetaCart
“Somebody says, ‘You know, you people always say that space is continuous. How do you know when you get to a small enough dimension that there really are enough points in between, that it isn’t just a lot of dots separated by little distances? ’ Or they say, ‘You know those quantum mechanical

The hierarchy problem and new dimensions at a millimeter

by Savas Dimopoulos, Gia Dvali, et al. , 2008
"... We propose a new framework for solving the hierarchy problem which does not rely on either supersymmetry or technicolor. In this framework, the gravitational and gauge interactions become united at the weak scale, which we take as the only fundamental short distance scale in nature. The observed wea ..."
Abstract - Cited by 664 (5 self) - Add to MetaCart
We propose a new framework for solving the hierarchy problem which does not rely on either supersymmetry or technicolor. In this framework, the gravitational and gauge interactions become united at the weak scale, which we take as the only fundamental short distance scale in nature. The observed

A review of image denoising algorithms, with a new one

by A. Buades, B. Coll, J. M. Morel - SIMUL , 2005
"... The search for efficient image denoising methods is still a valid challenge at the crossing of functional analysis and statistics. In spite of the sophistication of the recently proposed methods, most algorithms have not yet attained a desirable level of applicability. All show an outstanding perf ..."
Abstract - Cited by 508 (6 self) - Add to MetaCart
and their explanation as a violation of the image model; quantitative experimental: by tables of L 2 distances of the denoised version to the original image. The most powerful evaluation method seems, however, to be the visualization of the method noise on natural images. The more this method noise looks like a real

Divergence measures based on the Shannon entropy

by Jianhua Lin - IEEE Transactions on Information theory , 1991
"... Abstract-A new class of information-theoretic divergence measures based on the Shannon entropy is introduced. Unlike the well-known Kullback divergences, the new measures do not require the condition of absolute continuity to be satisfied by the probability distributions in-volved. More importantly, ..."
Abstract - Cited by 666 (0 self) - Add to MetaCart
, their close relationship with the variational distance and the probability of misclassification error are established in terms of bounds. These bounds are crucial in many applications of divergence measures. The new measures are also well characterized by the properties of nonnegativity, finiteness

A Simple, Fast, and Accurate Algorithm to Estimate Large Phylogenies by Maximum Likelihood

by Stéphane Guindon, Olivier Gascuel , 2003
"... The increase in the number of large data sets and the complexity of current probabilistic sequence evolution models necessitates fast and reliable phylogeny reconstruction methods. We describe a new approach, based on the maximumlikelihood principle, which clearly satisfies these requirements. The ..."
Abstract - Cited by 2182 (27 self) - Add to MetaCart
of 500 rbcL sequences with 1,428 base pairs from plant plastids, thus reaching a speed of the same order as some popular distance-based and parsimony algorithms. This new method is implemented in the PHYML program, which is freely available on our web page:

Semantic similarity based on corpus statistics and lexical taxonomy

by Jay J. Jiang, David W. Conrath - Proc of 10th International Conference on Research in Computational Linguistics, ROCLING’97 , 1997
"... This paper presents a new approach for measuring semantic similarity/distance between words and concepts. It combines a lexical taxonomy structure with corpus statistical information so that the semantic distance between nodes in the semantic space constructed by the taxonomy can be better quantifie ..."
Abstract - Cited by 873 (0 self) - Add to MetaCart
This paper presents a new approach for measuring semantic similarity/distance between words and concepts. It combines a lexical taxonomy structure with corpus statistical information so that the semantic distance between nodes in the semantic space constructed by the taxonomy can be better

Muscle: multiple sequence alignment with high accuracy and high throughput

by Robert C. Edgar - NUCLEIC ACIDS RES , 2004
"... We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the logexpectation score, and refinement using tree-dependent r ..."
Abstract - Cited by 2509 (7 self) - Add to MetaCart
We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the logexpectation score, and refinement using tree

Locally weighted learning

by Christopher G. Atkeson, Andrew W. Moore , Stefan Schaal - ARTIFICIAL INTELLIGENCE REVIEW , 1997
"... This paper surveys locally weighted learning, a form of lazy learning and memorybased learning, and focuses on locally weighted linear regression. The survey discusses distance functions, smoothing parameters, weighting functions, local model structures, regularization of the estimates and bias, ass ..."
Abstract - Cited by 599 (51 self) - Add to MetaCart
This paper surveys locally weighted learning, a form of lazy learning and memorybased learning, and focuses on locally weighted linear regression. The survey discusses distance functions, smoothing parameters, weighting functions, local model structures, regularization of the estimates and bias
Results 1 - 10 of 22,946