In this article we discuss artificial neural networks-based fault detection and isolation applications for robotic manipulators. The artificial neural networks (ANNs) are used for both residual generation and residual analysis. A multilayer perceptron (MLP) is employed to reproduce the dynamics of the robotic manipulator. Its outputs are compared with actual position and velocity measurements, ...

This paper presents a comparative study of the hybrid models, neural networks and nonparametric regression models in time series forecasting. The components of these hybrid models are consisting of the nonparametric regression and artificial neural networks models. Smoothing spline, regression spline and additive regression models are considered as the nonparametric regression components. Furth...

Faults in robotic manipulators can cause economic losses and serious damages. In this paper, two artificial neural networks are employed to provide FDI to robotic manipulators. The first is a multilayer perceptron trained with backpropagation utilized to reproduce the dynamic of the manipulator and, so, generate the residual vector. The second is a radial basis function network employed to clas...

The fuzzy and neuro fuzzy systems have been successfully used to solve problems in various fields such as medicine, manufacturing, control, agriculture and academic applications. In recent decades, neural networks have been used to the identification, assessment and diagnosis of diseases. In this thesis we performed a comparative study among fuzzy neural networks (ANFIS), multilayer perceptron ...

An iris pattern recognition system is developed for CASIA database using Singular Value Decomposition transform as a tool for feature extraction. Experimental prototype pattern recognition (PR) system is designed in which iris images of ten different persons are given as input to the system. After localizing region of interest (ROI), features are extracted with respect to image statistics, text...

This paper describes Weighted Radial Basis Functions, a neuro-fuzzy uni cation algorithm which mixes Perceptrons and Radial Basis Functions. The algorithm has been tested as a pattern classi er in practical applications. Its performance are compared against those of other neural classi ers. The proposed algorithm has performance comparable or better than other neural algorithms, although it can...

In this paper, we propose to use support vector machines for classification of bacterial growth and non growth database and modeling the probability of growth. Unlike artificial neural networks paradigms, support vector machines use the kernel functions and support vectors with maximum margin, which allows a better performance. As a practical application of the new approach, support vector mach...

This paper presents our experiences with the use of feed forward neural networks for piano chord recognition and polyphonic piano music transcription. Our final goal is to build a transcription system that would transcribe polyphonic piano music over the entire piano range. The central part of our system uses neural networks acting as pattern recognisers and extracting notes from the source aud...

Statistical, spectral, multi-resolution and non-linear methods were applied to heart rate variability (HRV) series linked with classification schemes for the prognosis of cardiovascular risk. A total of 90 HRV records were analyzed: 45 from healthy subjects and 45 from cardiovascular risk patients. A total of 52 features from all the analysis methods were evaluated using standard two-sample Kol...