Add to ORKGThis thesis studies various issues related to artificial neural networks for pattern recognition and function approximation with the aim to enhance its capability and to improve its performance. It proposes a novel method for globally finding good minima and optimizing the Correct Classification Rate(CCR), and a novel algorithm for network construction and weight initialization. The thesis also an-alyzes the fundamentals of Time-Delay Neural Network(TDNN) and presents an augmented TDNN (ATDNN) for frequency and scale invariant sequence classification.Master of Engineerin
This work describes the advantages and disadvantages of using neural networks for pattern recognitio...
This paper introduces a novel feedforward network called the pi-sigma network. This network utilizes...
DoctorIn this thesis, improving the performance of adaptive learning-rate algorithms in neural netwo...
This thesis studies various issues related to artificial neural networks for pattern recognition and...
This paper introduces a change in the structure of an artificial neuron (McCulloch and Pitts), to im...
Dynamic analysis of temporally changing signals is a key issue in real-time signal processing and un...
This dissertation studies neural networks for pattern classification and universal approximation. Th...
Title: Artificial neural networks for pattern recognition Author: Marek Kukačka Department: Katedra ...
Title: Artificial neural networks for pattern recognition Author: Marek Kukačka Department: Katedra ...
The Adaptive Time-delay Neural Network (AT N N), a paradigm for training a nonlinear neural network ...
In this thesis we investigate various aspects of the pattern recognition problem solving process. Pa...
In this thesis we investigate various aspects of the pattern recognition problem solving process. Pa...
This thesis studies the introduction of a priori structure into the design of learning systems based...
: Structure of incremental neural network (IncNet) is controlled by growing and pruning to match th...
This thesis investigates the functionality of the units used in connectionist Artificial Intelligenc...
This work describes the advantages and disadvantages of using neural networks for pattern recognitio...
This paper introduces a novel feedforward network called the pi-sigma network. This network utilizes...
DoctorIn this thesis, improving the performance of adaptive learning-rate algorithms in neural netwo...
This thesis studies various issues related to artificial neural networks for pattern recognition and...
This paper introduces a change in the structure of an artificial neuron (McCulloch and Pitts), to im...
Dynamic analysis of temporally changing signals is a key issue in real-time signal processing and un...
This dissertation studies neural networks for pattern classification and universal approximation. Th...
Title: Artificial neural networks for pattern recognition Author: Marek Kukačka Department: Katedra ...
Title: Artificial neural networks for pattern recognition Author: Marek Kukačka Department: Katedra ...
The Adaptive Time-delay Neural Network (AT N N), a paradigm for training a nonlinear neural network ...
In this thesis we investigate various aspects of the pattern recognition problem solving process. Pa...
In this thesis we investigate various aspects of the pattern recognition problem solving process. Pa...
This thesis studies the introduction of a priori structure into the design of learning systems based...
: Structure of incremental neural network (IncNet) is controlled by growing and pruning to match th...
This thesis investigates the functionality of the units used in connectionist Artificial Intelligenc...
This work describes the advantages and disadvantages of using neural networks for pattern recognitio...
This paper introduces a novel feedforward network called the pi-sigma network. This network utilizes...
DoctorIn this thesis, improving the performance of adaptive learning-rate algorithms in neural netwo...