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The paper justifies the necessity to use the hand writer identification using the feed forward neural networks. Identifying the authors of a handwritten sample using automatic image-based processing methods is an interesting pattern recognition problem with direct applicability in the legal and historic documents. Leading a worrisome life among the harder forms of biometrics, the identification of...
This paper investigates how to extend ability of feed forward neural network for purposes of musical note visualization and F0 estimation. We set experiments to find the best features that introduce high generalization rate and good F0 estimation result per single audio frame. These features were extracted from spectral data, autocorrelation, auditory filter bank, and modified Ceptral methods. The...
This paper demonstrates the function approximation capability of feed forward neural network (FFNN). An attempt has been made to develop the Graphical user Interface (GUI) system for function approximation. This GUI system can handle the function approximation of any nonlinear/linear function which can have any number of input variable and 6 output variables. Parameters of neural network can be set...
Intrusion Detection is the task of detecting, preventing and possibly reacting to the attack and intrusions in a network based computer systems. In the literature several machine-learning paradigms have been proposed for developing an Intrusion Detection System. This paper proposes an Artificial Neural Network approach for Intrusion Detection. A Feed Forward Neural Network trained by Back Propagation...
Early warning systems are critical in providing emergency response in the event of unexpected hazards. Cheap cameras and improvements in memory and computing power have enabled the design of fire detectors using video surveillance systems. This is critical in scenarios where traditional smoke detectors cannot be installed. In such scenarios, it has been observed that the smoke is visible well before...
Demand Side Management (DSM) programs consist of the scheduling, planning, executing and monitoring activities of load demand in such a way to ensure the load side management at utilities as well as consumers' levels. The main objective of DSM is optimizing the utilization of available electricity. In developing countries like Pakistan the importance of DSM has increased significantly due to considerable...
The paper investigates the feasibility of implementing an intelligent classifier for noise sources in the ocean, with the help of artificial neural networks, using higher order spectral features. Non-linear interactions between the component frequencies of the noise data can give rise to certain phase relations called Quadratic Phase Coupling (QPC), which cannot be characterized by power spectral...
This paper presents an application of Artificial Neural Network (ANN) for monitoring transient stability assessment (TSA) considering system topology changes. Offline trained ANN makes use of the advance of online TSA in specifying the proper remedial action for real time power system operation to counteract the system instability. The training of ANN is executed using important selected features...
In this paper, a new back propagation (BP) algorithm with adaptive momentum is proposed, where the momentum coefficient is adjusted iteratively based on the current descent direction and the weight increment in the last iteration. A convergence result of the algorithm is presented when it is used for training feed forward neural networks (FNNs) with a hidden layer. Simulation results have shown that...
The PCB traces produce electromagnetic field when excited by a signal source. The trace acts as a source of emission when impedance mismatch or a discontinuity along the length of the trace occurs which may interfere with other equipments placed in its closer proximity. In this paper a two stage feed forward neural network using Back Propagation algorithm is used to identify the radiating trace. The...
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