Classification of run-length encoded binary data (2007)
Babua, Ravindra T, Murty, Narasimha M, Agrawal, VK
In classification of binary featured data, distance computation is carried out by considering each feature. We represent the given binary data as run-length encoded data. This would lead to a compact...
A New ATPG Technique (ExpoTan) for Testing Analog Circuits (2007)
Varaprasad, BKSVL, Patnaik, LM, Jamadagni, HS, Agrawal, VK
In analog testing, usage of a single sinusoid as a test signal when compared to multitone signal, and fault detection with digital counting technique, facilitate the test implementation with simple...
Classification of run-length encoded binary data (2007)
Babua, Ravindra T, Murty, Narasimha M, Agrawal, VK
In classification of binary featured data, distance computation is carried out by considering each feature. We represent the given binary data as run-length encoded data. This would lead to a compact...
A New ATPG Technique (ExpoTan) for Testing Analog Circuits (2007)
Varaprasad, BKSVL, Patnaik, LM, Jamadagni, HS, Agrawal, VK
In analog testing, usage of a single sinusoid as a test signal when compared to multitone signal, and fault detection with digital counting technique, facilitate the test implementation with simple...
Hybrid Learning Scheme for Data Mining Applications (2004)
Babu, Ravindra T, Murty, Narasimha M, Agrawal, VK
Classification of large datasets is a challenging task in data mining. In the current work, we propose a novel method that compresses the data and classifies the test data directly in its compressed...
Adaptive Boosting with Leader Based Learners for Classification of Large Handwritten Data (2004)
Babu, Ravindra T, Murty, Narasimha M, Agrawal, VK
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for adaptive boosting method, consists of repeated use of a weak or a base learning algorithm to...
Hybrid Learning Scheme for Data Mining Applications (2004)
Babu, Ravindra T, Murty, Narasimha M, Agrawal, VK
Classification of large datasets is a challenging task in data mining. In the current work, we propose a novel method that compresses the data and classifies the test data directly in its compressed...
Adaptive Boosting with Leader Based Learners for Classification of Large Handwritten Data (2004)
Babu, Ravindra T, Murty, Narasimha M, Agrawal, VK
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for adaptive boosting method, consists of repeated use of a weak or a base learning algorithm to...
Correlated X-ray timing and spectral behavior in GX 349+2 (2003)
We present a detailed and systematic investigation of correlated spectral and timing properties of the Z source GX 349+2, using extensive data (\sim221 ks) obtained from the...
The state of VLSI testing (2002)
Patnaik, LM, Jamadagni, HS, Agrawal, VK, Varaprasad, BKSVL
The phenomenal development in electronic systems has, in large part, the advances in Very Large Scale of Integration (VLSI) semiconductor technologies to thank. Performance, area, power and testing...
The state of VLSI testing (2002)
Patnaik, LM, Jamadagni, HS, Agrawal, VK, Varaprasad, BKSVL
The phenomenal development in electronic systems has, in large part, the advances in Very Large Scale of Integration (VLSI) semiconductor technologies to thank. Performance, area, power and testing...
Genetic programming based pattern classification with feature space partitioning (2001)
Kishore, JK, Patnaik, LM, Mani, V, Agrawal, VK
Genetic programming (GP) is an evolutionary technique and is gaining attention for its ability to learn the underlying data relationships and express them in a mathematical manner. Although GP uses...
Genetic programming based pattern classification with feature space partitioning (2001)
Kishore, JK, Patnaik, LM, Mani, V, Agrawal, VK
Genetic programming (GP) is an evolutionary technique and is gaining attention for its ability to learn the underlying data relationships and express them in a mathematical manner. Although GP uses...
Application of Genetic Programming for Multicategory Pattern Classification (2000)
Kishore, JK, Patnaik, LM, Mani, V, Agrawal, VK
This paper explores the feasibility of applying genetic programming (GP) to multicategory pattern classification problem for the first time. GP can discover relationships among observed data and...
Application of Genetic Programming for Multicategory Pattern Classification (2000)
Kishore, JK, Patnaik, LM, Mani, V, Agrawal, VK
This paper explores the feasibility of applying genetic programming (GP) to multicategory pattern classification problem for the first time. GP can discover relationships among observed data and...