Abstract: Proton exchange membrane fuel cells (PEMFCs) can be used in transportation, power plants and distributed generation due to high power density and fast speed of operation. Dynamic modeling of fuel cells is a primary need for performance assessment studies of real-time and controller design. Some new models of Simulink use artificial intelligence for making graph output model. Neural network is one of these models. Neural network just uses input – output data that has obtained in several experiments and does not need to set all the parameters. In this paper, first, the PEMFC has been simulated using feedforward neural networks. This network has been trained using different algorithms and the results were compared to determine the appropriate algorithm by MADM methods. Then the effect of destructive signal on the neural network is evaluated and the authors are attempted to reduce this effect by developing a suitable adaptive filte

• Publication Date: 23-Jun-2012
• DOI: 10.15224/978-981-07-2683-6-103
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Abstract: Wireless multimedia has created boom in today’s era. It is just a fraction of seconds to get information at any time anywhere. All these because of the development of multicarrier communication system, OFDM, which provides high data rate as well as high speed. With that channel estimation becomes more challenging. In such multicarrier systems the time varying channel is often estimated based on different algorithms. These algorithms are basically categorised as blind and non-blind channel estimation techniques. Due to the limitations of blind algorithms such as requirement of the statistical knowledge of received signal, the non-blind i.e. pilot aided channel estimation have become more popular. In such techniques known symbols to the receiver called pilots are inserted in the OFDM data symbols and they should be close enough to fulfil the Nyquist sampling theorem for pilot spacing [1]. This paper shows the simulation results to prove the sampling on the channel estimatio

• Publication Date: 23-Jun-2012
• DOI: 10.15224/978-981-07-2683-6-104
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• Downloads: 0