Adaptation Of Memory Depth In The Gamma Filter (1998)
Gamma filter is a special class of generalized feedforward filters where feedbacks are allowed only locally. We present the conditions for the selection of optimal parameters which are the weights...
Learning to Generate a Sinewave with a Recurrent TwoNeuron Network (1998)
Jyh-ming Kuo, Jose C. Principe
this paper, we study an autonomous two-processing-element (PE) network and propose a method to decompose the task of determining the network parameters. The theoretical analysis and experimental...
Reconstructed Dynamics and Chaotic Signal Modeling (1998)
Jyh-ming Kuo, Jose C. Principe
: A nonlinear AR model is derived from the reconstructed dynamics of a signal. The underlying system is assumed to be nonlinear, autonomous, and determinstic. In this formulation, the output error...
Dynamic Modelling of Chaotic Time Series with Neural Networks (1998)
Jose C. Principe, Jyh-ming Kuo
This paper discusses the use of artificial neural networks for dynamic modelling of time series. We argue that multistep prediction is more appropriate to capture the dynamics of the underlying...
Prediction of Chaotic Time Series Using Recurrent Neural Networks (1998)
Jyh-ming Kuo, Jose C. Principe, Bert Devries
In this paper, we propose to train and use a recurrent artificial neural network(ANN) to predict a chaotic time series. Instead of predicting the next sample in the time series as is normally done,...
Backpropagation Through Time with Fixed Memory Size Requirements (1998)
U. Of Florida, Jose C. Principe, Jyh-ming Kuo
this memory (memory traces) are convolutions of the input with E w ij
Noise reduction in state space using the Focused Gamma Neural Network (1998)
Jose C. Principe, Jyh-ming Kuo
In this paper we utilize the gamma neural model to improve the signal to noise ratio (SNR) of broadband signals corrupted by white noise. The projection of a noisy signal onto the signal subspace can...
Modeling Applications with the Focused Gamma Net (1998)
Jose C. Principe, Bert De Vries, Jyh-ming Kuo, Pedro Guedes De Oliveira
The focused gamma network is proposed as one of the possible implementations of the gamma neural model. The focused gamma network is compared with the focused backpropagation network and TDNN for a...
Prediction of Chaotic Time Series with Neural Networks (1998)
Jose C. Principe, Alok Rathie, Jyh-ming Kuo
This paper shows that the dynamics of nonlinear systems that produce complex time series can be captured in a model system. The model system is an artificial neural network, trained with...
Analysis of Short Term Memories for Neural Networks (1998)
Jose C. Principe, Hui-h. Hsu, Jyh-ming Kuo
Short term memory is indispensable for the processing of time varying information with artificial neural networks. In this paper a model for linear memories is presented, and ways to include memories...