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University of Siegen
(8 results)-
White Papers
Iterative Method for Improvement of Coding and Decryption
July 1, 2009, 12:00am PDT
Cryptographic check values (digital signatures, MACs and H-MACs) are useful only if they are free of errors. For that reason all of errors in cryptographic check values should be corrected after...
Provided by University of Siegen
-
White Papers
A Neural Network Classifier of Volume Datasets
June 12, 2009, 12:00am PDT
Many state-of-the art visualization techniques must be tailored to the specific type of dataset, its modality (CT, MRI, etc.), the recorded object or anatomical region (head, spine, abdomen, etc.)...
Provided by University of Siegen
-
White Papers
Concatenation and Turbo Principle of Channel Coding and Cryptography
October 1, 2008, 12:00am PDT
The transmission of data coded by a convolutional or turbo code and secured by cryptographic check values is improved by using of Soft Input Decryption. An additional coding gain can be reached,...
Provided by University of Siegen
-
White Papers
Method to Improve Channel Coding Using Cryptography
June 17, 2009, 12:00am PDT
A new approach for the improvement of coding gain in channel coding using Advanced Encryption Standard (AES) and Maximum A Posteriori (MAP) algorithm is proposed. This new approach uses the...
Provided by University of Siegen
-
White Papers
Parallel Joint Channel Coding and Cryptography
June 17, 2009, 12:00am PDT
Method of Parallel Joint Channel Coding and Cryptography has been analyzed and simulated in this paper. The method is an extension of Soft Input Decryption with feedback, which is used for...
Provided by University of Siegen
-
White Papers
Feature Selection for Improving the Usability of Classification Results of High-Dimensional Data
May 6, 2008, 12:00am PDT
The semiconductor industry is one of the many fields of applications, where the usage of computational tools is inevitable in order to analyze huge amounts of data. As quality demands and...
Provided by University of Siegen
-
Whitepapers
Distributed Duty Cycling Optimization for Asynchronous Wireless Sensor Networks
May 24, 2012, 12:00am PDT
One of the major sources of energy waste in a Wireless Sensor Network (WSN) is idle listening, i.e., the cost of actively listening for potential packets. This paper focuses on reducing the...
Provided by University of Siegen
-
White Papers
Language Composition Untangled
February 3, 2012, 12:00am PST
In language-oriented programming and modeling, software developers are largely concerned with the definition of domain-specific languages (DSLs) and their composition. While various implementation...
Provided by University of Siegen
-
Whitepapers
Distributed Duty Cycling Optimization for Asynchronous Wireless Sensor Networks
May 24, 2012, 12:00am PDT
One of the major sources of energy waste in a Wireless Sensor Network (WSN) is idle listening, i.e., the cost of actively listening for potential packets. This paper focuses on reducing the...
Provided by University of Siegen
-
White Papers
Language Composition Untangled
February 3, 2012, 12:00am PST
In language-oriented programming and modeling, software developers are largely concerned with the definition of domain-specific languages (DSLs) and their composition. While various implementation...
Provided by University of Siegen
-
White Papers
Feature Selection for Improving the Usability of Classification Results of High-Dimensional Data
May 6, 2008, 12:00am PDT
The semiconductor industry is one of the many fields of applications, where the usage of computational tools is inevitable in order to analyze huge amounts of data. As quality demands and...
Provided by University of Siegen
-
White Papers
Parallel Joint Channel Coding and Cryptography
June 17, 2009, 12:00am PDT
Method of Parallel Joint Channel Coding and Cryptography has been analyzed and simulated in this paper. The method is an extension of Soft Input Decryption with feedback, which is used for...
Provided by University of Siegen
-
White Papers
Method to Improve Channel Coding Using Cryptography
June 17, 2009, 12:00am PDT
A new approach for the improvement of coding gain in channel coding using Advanced Encryption Standard (AES) and Maximum A Posteriori (MAP) algorithm is proposed. This new approach uses the...
Provided by University of Siegen
-
White Papers
Concatenation and Turbo Principle of Channel Coding and Cryptography
October 1, 2008, 12:00am PDT
The transmission of data coded by a convolutional or turbo code and secured by cryptographic check values is improved by using of Soft Input Decryption. An additional coding gain can be reached,...
Provided by University of Siegen
-
White Papers
A Neural Network Classifier of Volume Datasets
June 12, 2009, 12:00am PDT
Many state-of-the art visualization techniques must be tailored to the specific type of dataset, its modality (CT, MRI, etc.), the recorded object or anatomical region (head, spine, abdomen, etc.)...
Provided by University of Siegen
-
White Papers
Iterative Method for Improvement of Coding and Decryption
July 1, 2009, 12:00am PDT
Cryptographic check values (digital signatures, MACs and H-MACs) are useful only if they are free of errors. For that reason all of errors in cryptographic check values should be corrected after...
Provided by University of Siegen
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