Tham khảo tài liệu 'power quality monitoring analysis and enhancement part 5', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Application of Signal Processing in Power Quality Monitoring 87 sampling frequency used in Lu et al. 2005 is 5 kHz and the noisy condition where signal to noise ratio value is about 26 dB is considered. 5. Classification techniques Feed Forward Neural Networks FFNN Neural networks are composed of simple elements operating in parallel. These elements are inspired by biological nervous systems. As in nature the connections between elements largely determine the network function. Neural networks can be trained to perform a particular function by adjusting the values of the connections weights and biases between elements. Generally neural networks are adjusted or trained so that a particular input leads desired target output. The network is adjusted based on a comparison of the output and the target until the network output matches the target. Usually many such input target pairs are needed to train a network. Neural networks have been trained to perform complex functions in various fields including pattern recognition identification classification speech vision and control systems. Neural networks can also be trained to solve problems that are difficult for conventional computers or human beings. Neural networks are usually applied for one of the three following goals Training a neural network to fit a function Training a neural network to recognize patterns Training a neural network to cluster data The training process requires a set of examples of proper network behavior . network inputs and target outputs. During training the weights and biases of the network are iteratively adjusted to minimize the network performance function Moravej et al. 2002 . Radial Basis Function Network RBFN The RBFN model Mao et al. 2000 consists of three layers the inputs and hidden and output layers. The input space can either be normalized or an actual representation can be used. This is then fed to the associative cells of the hidden layer which acts as a transfer function.
