... nodes of the SRWNN Soheil Ganjefar can be contacted at: s_ganjefar@yahoo.com © Emerald Group Publishing Limited 2012 Power system stabilizer Intelligent PID controller Self‐recurrent wavelet neural network Adaptive learning rates Chaotic optimization Neural nets Programming...

... transforms Neural nets Electric machines For the highly dynamical behavior of the induction machine operated under any kind of field‐oriented control (FOC), a position sensor (encoder) is needed. Research was placed on omitting this sensor using fundamental machine models but as the mathematical...

... at: xudekai1983@sina.com © Emerald Group Publishing Limited 2010 Wireless Sensors Networks Neural nets Fault diagnosis of wireless sensor networks (WSN) nodes are fault‐tolerant design technology. WSN nodes on fault diagnosis divided into centralized (Nithya et al., 2005...

... model can be obtained through least square method. Define model error as e_ω=ω−ω_m. Neural nets Control systems Adaptive system theory In servo‐system control, due to the nonlinearity, variation, uncertainty...

.../value As the reliability of the optimum solution is strongly affected by the accuracy of the neural approximation model, the approximation error is kept as low as possible, especially in the maximum/minimum points. © Emerald Group Publishing Limited 2009 Functional analysis Neural nets...

... Limited 2009 Control systems Vibration Electric motors Neural nets Estimation In many industrial drives, like rolling‐mill, conveyer belt or cage host drives, modern servo‐drives, robot‐arm or even in computer disc drives, the elasticity of a shaft between the motor and load machine...

... reduction. © Emerald Group Publishing Limited 2008 Torque Electric motors Neural nets Electromagnetism Owing to high‐power density and high‐torque/inertia ratio, permanent magnet synchronous motor (PMSM) are widely used in high‐performance drives such as electrical vehicles, robotic...

...: _K^_ represents an integral operator; J ′ represents an equivalent electric surface current; the superscripts int and ext refer to the field inside the cavity and in the free space, respectively. © Emerald Group Publishing Limited 2008 Boundary‐elements methods Neural nets...

... the objective functions and constraints critically were selected: (1) Length of stator stack (m) x1 (2) Width of stator slot (m) x2 © Emerald Group Publishing Limited 2007 Neural nets Software prototyping Fuzzy logic Programming and algorithm theory Optimum design...

.... Such efficient modeling can directly help in improving and optimizing the Torus motor drive system design. Originality/value It demonstrates that ANFIS can model the nonlinear behavior of the back EMF of the Torus motor with excellent accuracy. © Emerald Group Publishing Limited 2007 Neural nets...

... Publishing Limited 2007 Benchmarking Neural nets Optimization techniques Some analytical benchmarks are available to compare the performances of multi‐objective optimisation methods (Deb et al., 2005). However, in case of electromagnetic optimisation problems, analytical...

... and voltage sensors (LEM) and an encoder. Motion Control systems Magnetic devices Neural nets Demand for using permanent magnet synchronous motors (PMSMs) in industrial drives has risen sharply in the last decade due to such favourable features of PMSMs as high power factor, high torque...

... are updated according to the minimization of the total error function (Haykin, 1994). © Emerald Group Publishing Limited 2005 Neural nets Fuzzy logic Control Solar power Solar energy conversion has various advantages such as short time duration of installation and operation, circuit...

... is able to find a point belonging to such an intersection. Optimization techniques Neural nets Magnetic devices The optimal design of electromagnetic devices is a very difficult task, because of the very complex implicit relationship between the design parameters and the field distribution...

.... The important problem is thus the generation of the features best representing the individual beats, i.e. suppressing the differences among the beats belonging to the same class and differing the beats of different classes as much as possible. © Emerald Group Publishing Limited 2005 Neural nets...

...) are initialized to small random values. © Emerald Group Publishing Limited 2005 Electromagnetic fields Pipelines Neural nets Electromagnetic interference effects of transmission lines on nearby gas pipelines are a real problem that can place both operator safety and pipeline integrity...

... Limited 2005 Numerical analysis Neural nets Dielectric properties Recently, microwave power engineers have taken a particular interest in complex permittivity, ε=ε′−iε″. While modern electromagnetic simulators allow the engineers to extensively characterize...

... is increased. © Emerald Group Publishing Limited 2004 Inductance Loading (physics) Wavelengths Voltage fluctuations Neural nets Transient response Detection and measurement of voltage sags and transient voltages must be accurate enough to determine the cause of the disturbances...

... Noise Microwaves Neural nets Neural net devices Microwave transistors The use of neural networks in modeling, optimization and simulation of electronic circuits is a relatively new and very attractive approach (Haykin, 1994). Recently, neural networks are applied in the area of microwave...