Outlier detection has many important applications in the field of fraud detection, network robustness analysis and intrusion detection. Some researches have utilized the neural network to solve the problem because it has the advantage of powerful modeling ability. In this paper, we propose a RBF neural network model using subtractive clustering algorithm for selecting the hidden node centers, w...

Filtering of signals is of primary importance in signal processing. The design of filters to perform signal estimation is a problem that freeze up in the design of communication systems, control systems, in geophysics & in many other applications & disciplines. Optimum filters are proposed for filtering. In this paper, neural networks have been trained to filter satisfactorily with specified MS...

in this study, a new adaptive controller is proposed for position control of pneumatic systems. difficulties associated with the mathematical model of the system in addition to the instability caused by pulse width modulation (pwm) in the learning-based controllers using gradient descent, motivate the development of a new approach for pwm pneumatics. in this study, two modified feedback error l...

. This paper devoted to an iris recognition system (IRS) designed using 2D-Discrete Cosine Transform (DCT) features and Self Organizing Map (SOM) and Radial Basis Function (RBF) which are an Artificial Neural Network (ANN) used as classifier. DCT is used for feature extraction to capture essential details. SOM and RBF are applied for classification with different functional paradigms. With resp...

In this study the impact of a Radio-over-Fiber (RoF) subsystem on the performance of Orthogonal Frequency Division Multiplexing (OFDM) system is evaluated. The study investigates the use of Multi-Layered Perceptron (MLP) and Radial Basis Function (RBF) neural networks to compensate for the optical subsystem nonlinearities in terms of bit error rate, error vector magnitude, and computational com...