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85,876
Regularization Theory and Neural Networks Architectures
- Neural Computation
, 1995
"... We had previously shown that regularization principles lead to approximation schemes which are equivalent to networks with one layer of hidden units, called Regularization Networks. In particular, standard smoothness functionals lead to a subclass of regularization networks, the well known Radial Ba ..."
Abstract
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Cited by 395 (32 self)
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Basis Functions approximation schemes. This paper shows that regularization networks encompass a much broader range of approximation schemes, including many of the popular general additive models and some of the neural networks. In particular, we introduce new classes of smoothness functionals that lead
Handwritten Character Recognition Using Neural Network Architectures
- In Proceedings of the 4th United States Postal Service Advanced Technology Conference
, 1990
"... We have developeda neural-network architecture for recognizing ..."
Abstract
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Cited by 1 (1 self)
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We have developeda neural-network architecture for recognizing
Neural network architecture for control
- IEEE Contr. Syst. Mag
, 1988
"... ABSTRACT: Two important computational features of neural networks are (1) associa-tive storage and retrieval of knowledge and (2) uniform rate of convergence of network dynamics, independent of network dimen-sion. This paper indicates how these prop-erties can be used for adaptive control through th ..."
Abstract
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Cited by 9 (0 self)
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ABSTRACT: Two important computational features of neural networks are (1) associa-tive storage and retrieval of knowledge and (2) uniform rate of convergence of network dynamics, independent of network dimen-sion. This paper indicates how these prop-erties can be used for adaptive control through
Neural Network Architectures for Diagnosis and . . .
, 1996
"... This paper presents a neural network that is able to give, together with the rotor fault diagnosis, the combined rotor-lead inertia momentum of an induction machine. The inputs of the network are the spectral components of machine input currents, speed and torque. A specific neural network architect ..."
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This paper presents a neural network that is able to give, together with the rotor fault diagnosis, the combined rotor-lead inertia momentum of an induction machine. The inputs of the network are the spectral components of machine input currents, speed and torque. A specific neural network
A Neural Network Architecture for Self-Organization of Object Understanding
- In: Proc. of Int. Scient. Coll'94, Ilmenau
, 1994
"... This paper describes the essentials of the whole neural network architecture. ..."
Abstract
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Cited by 2 (1 self)
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This paper describes the essentials of the whole neural network architecture.
Robust Artificial Neural Network Architectures
"... Abstract — Many artificial intelligence (AI) techniques are inspired by problem-solving strategies found in nature. Robustness is a key feature in many natural systems. This paper studies robustness in artificial neural networks (ANNs) and proposes several novel, nature inspired ANN architectures. T ..."
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Abstract — Many artificial intelligence (AI) techniques are inspired by problem-solving strategies found in nature. Robustness is a key feature in many natural systems. This paper studies robustness in artificial neural networks (ANNs) and proposes several novel, nature inspired ANN architectures
Neural Network Architecture for 3D Object Representation
"... The paper discusses a neural network architecture for 3D object modeling. A multi-layered feedforward structure having as inputs the 3D-coordinates of the object points is employed to model the object space. Cascaded with a transformation neural network module, the proposed architecture can be used ..."
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The paper discusses a neural network architecture for 3D object modeling. A multi-layered feedforward structure having as inputs the 3D-coordinates of the object points is employed to model the object space. Cascaded with a transformation neural network module, the proposed architecture can be used
A Neural Network Architecture for Syntax Analysis
, 1999
"... Artificial neural networks (ANN's), due to their inherent parallelism, offer an attractive paradigm for implementation of symbol processing systems for applications in computer science and artificial intelligence. This paper explores systematic synthesis of modular neural-network architectures ..."
Abstract
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Cited by 9 (1 self)
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Artificial neural networks (ANN's), due to their inherent parallelism, offer an attractive paradigm for implementation of symbol processing systems for applications in computer science and artificial intelligence. This paper explores systematic synthesis of modular neural-network architectures
SELECTING NEURAL NETWORK ARCHITECTURE FOR INVESTMENT PROFITABILITY PREDICTIONS
"... Abstract: In this paper we present a modified neural network architecture and an algorithm that enables neural networks to learn vectors in accordance to user designed sequences or graph structures. This enables us to use the modified network algorithm to identify, generate or complete specified pat ..."
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Abstract: In this paper we present a modified neural network architecture and an algorithm that enables neural networks to learn vectors in accordance to user designed sequences or graph structures. This enables us to use the modified network algorithm to identify, generate or complete specified
Results 1 - 10
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85,876
