The planar thallium-201 myocardial perfusion scintigram is a widely used diagnostic technique for detecting and estimating the risk of coronary artery disease. Neural networks learned to interpret 100 thallium scintigrams as determined by individual expert ratings. Standard error backpropagation was compared to standard LMS, and LMS combined with one layer of RBF units. Using the "leave-one-out...

To reduce the Gaussian noise from Magnetic Resonance Image (MRI) corrupted during their acquisition process, we propose a filtering method based RBF neural network. Indeed, the Gaussian noise is considered and formulated as constraints in an energy functional base on minimization of Total Variation (TV). In the RBF training stage, the backprobagation algorithm is used to solve the TV functional...

Solubility data of solid in aqueous and different organic solvents are very important physicochemical properties considered in the design of the industrial processes and the theoretical studies. In this study, experimental solubility data of 666 pharmaceutical compounds in water and 712 pharmaceutical compounds in organic solvents were collected from different sources. Three different artificia...

Based on MATLAB, a new model-BRF network model is founded to be used in groundwater dynamic simulation and prediction. It is systematically studied about the training sample set, testing sample set, the pretreatment of the original data, neural network construction, training, testing and evaluating the entire process. A favorable result is achieved by applying the model to simulate and predict ...

Neural network process modelling needs the use of experimental design and studies. A new neural network constructive algorithm is proposed. Moreover, the paper deals with the influence of the parameters of radial basis function neural networks and multilayer perceptrons network in process modelling. Particularly, it is shown that the neural modelling, depending on learning approach, cannot be a...

This work proposes a neural-fuzzy sliding mode control scheme for a hydro-turbine speed governor system. Considering the assumption of elastic water hammer, a nonlinear mode of the hydro-turbine governor system is established. By linearizing this mode, a sliding mode controller is designed. The linearized mode is subject to uncertainties. The uncertainties are generated in the process of linear...

Recent experimental evidences have shown that because of a fast convergence and a nice accuracy, neural networks training via extended kalman filter (EKF) method is widely applied. However, as to an uncertainty of the system dynamics or modeling error, the performance of the method is unreliable. In order to overcome this problem in this paper, a new finite impulse response (FIR) filter based l...

This paper introduces a neural network approach to the problem of ore grade estimation. The system under consideration consists of three neural network modules each responsible for a different area of the deposit, depending on the sampling density. Octant and quadrant search is used as a way of presenting input patterns to the modules. Both radial basis function networks and multi-layered perce...