• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations

Tools

Sorted by:
Try your query at:
Semantic Scholar Scholar Academic
Google Bing DBLP
Results 1 - 10 of 6,966
Next 10 →

Convolutional codes with maximum distance profile

by Ryan Hutchinson, Roxana Smarandache, Joachim Rosenthal - Syst. Contr. Lett , 2005
"... Maximum distance profile codes are characterized by the property that two trajectories which start at the same state and proceed to a different state will have the maximum possible distance from each other relative to any other convolutional code of the same rate and degree. In this paper we use met ..."
Abstract - Cited by 19 (5 self) - Add to MetaCart
Maximum distance profile codes are characterized by the property that two trajectories which start at the same state and proceed to a different state will have the maximum possible distance from each other relative to any other convolutional code of the same rate and degree. In this paper we use

under the maximum distance

by Torleiv Kløve , 2009
"... The size of spheres of multipermutations ..."
Abstract - Add to MetaCart
The size of spheres of multipermutations

Maximum Distance Separable Convolutional Codes

by Joachim Rosenthal, Roxana Smarandache - APPL. ALGEBRA ENGRG. COMM. COMPUT , 1998
"... A maximum distance separable (MDS) block code is a linear code whose distance is maximal among all linear block codes of rate k/n. It is well known that MDS block codes do exist if the field size is more than n. In this paper we generalize this concept to the class of convolutional codes of a fixed ..."
Abstract - Cited by 40 (10 self) - Add to MetaCart
A maximum distance separable (MDS) block code is a linear code whose distance is maximal among all linear block codes of rate k/n. It is well known that MDS block codes do exist if the field size is more than n. In this paper we generalize this concept to the class of convolutional codes of a fixed

On the graphs with maximum distance on k-diameter

by Christine S. Swart, Henda C. Swart
"... The distance of a set of vertices is the sum of the distances between pairs of vertices in the set. We define the k-diameter of a graph as the maximum distance of a set of k vertices; so the 2-diameter is the normal diameter and the n-diameter where n is the order is the distance of the graph. We co ..."
Abstract - Cited by 2 (1 self) - Add to MetaCart
The distance of a set of vertices is the sum of the distances between pairs of vertices in the set. We define the k-diameter of a graph as the maximum distance of a set of k vertices; so the 2-diameter is the normal diameter and the n-diameter where n is the order is the distance of the graph. We

On Almost Maximum Distance Separable Codes

by N A M Al-Seraji , 2013
"... Abstract The main goal of this paper is to make link between the subjects of projective geometry, vector space and linear codes. The properties of codes and some examples are shown. Furthermore, we will give some information about the geometrical structure of the arcs. All these arcs are give rise ..."
Abstract - Add to MetaCart
to an error-correcting code that corrects the maximum possible number of errors for its length.

Maximum Distance Separable Symbol-Pair Codes

by Yeow Meng Chee, Han Mao Kiah, Chengmin Wang
"... Abstract—We study (symbol-pair) codes for symbol-pair read channels introduced recently by Cassuto and Blaum (2010). A Singleton-type bound on symbol-pair codes is established and infinite families of optimal symbol-pair codes are constructed. These codes are maximum distance separable (MDS) in the ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
Abstract—We study (symbol-pair) codes for symbol-pair read channels introduced recently by Cassuto and Blaum (2010). A Singleton-type bound on symbol-pair codes is established and infinite families of optimal symbol-pair codes are constructed. These codes are maximum distance separable (MDS

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 distance-based and parsimony approaches. The reduction of computing time is dramatic in comparison with other maximum-likelihood packages, while the likelihood maximization ability tends to be higher. For example, only 12 min were required on a standard personal computer to analyze a data set consisting

Maximum distance-gradient for robust image registration

by Rui Gan, Albert C. S. Chung, Shu Liao , 2008
"... To make up for the lack of concern on the spatial information in the conventional mutual information based image registration framework, this paper designs a novel spatial feature field, namely the maximum distance-gradient (MDG) vector field, for registration tasks. It encodes both the local edge i ..."
Abstract - Cited by 7 (1 self) - Add to MetaCart
To make up for the lack of concern on the spatial information in the conventional mutual information based image registration framework, this paper designs a novel spatial feature field, namely the maximum distance-gradient (MDG) vector field, for registration tasks. It encodes both the local edge

Maximum Distance Band Selection of Hyperspectral Images

by Shahram Latifi, Steven Wilson
"... Hyperspectral Imaging has been advanced by recent improvements in airborne imaging hardware. Early airborne HSI datasets such as Indian Pines, have a relatively low spatial and spectral resolution and are useful primarily for research purposes. Higher resolution and lower sensor noise has become the ..."
Abstract - Add to MetaCart
algorithms. The purpose of this research is to propose a method of maximum distance automated band selection in order to preprocess hyperspectral image cube data, and present the results when compared to those using the entire data set. The goal is to significantly increase the accuracy of target detection

Fast Algorithm for Finding Maximum Distance with Space Subdivision in E2

by Vaclav Skala, Zuzana Majdisova
"... Abstract. Finding an exact maximum distance of two points in the given set is a fundamental computational problem which is solved in many applications. This paper presents a fast, simple to implement and robust algorithm for finding this maximum distance of two points in E2. This algorithm is based ..."
Abstract - Add to MetaCart
Abstract. Finding an exact maximum distance of two points in the given set is a fundamental computational problem which is solved in many applications. This paper presents a fast, simple to implement and robust algorithm for finding this maximum distance of two points in E2. This algorithm is based
Next 10 →
Results 1 - 10 of 6,966
Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University