The paper presents a new transform, called vector-gradient Hough transform, for identifying elongated shapes in gray-scale images. This goal is achieved not only by collecting information on the edges of the objects, but also by reconstructing their transversal profile of luminosity. The main features of the new approach are related to its vector space formulation and the associated capability of exploiting all the vector information of the luminosity gradient.

The paper introduces the vector-gradient Hough transform (VGHT), a modified version of the gradient weighted Hough transform (GWHT), defined in vector space and able to exploit all the vector information of the gradient of luminosity. The new formulation, directly derived from the Radon transform, is analyzed and compared with the GWHT, in order to point out the improvement in selectivity provided by the VGHT in a strictly polar parametric space, without any relevant increase in computational complexity. This approach can be very suitable for identifying a specifically defined model of shapes in gray level images, ideally generated by a translation in the 2D space of a 1D luminosity profile. Finally, the suitability of the VGHT in real applications is shown with examples in the area of defect identification for automated visual inspection.

The authors present a computationally efficient unified approach to the numerical simulation of sensitivity and noise in majority-carrier semiconductor devices that is based on the extension to device simulation of the adjoint method for sensitivity and noise analysis of electrical networks. Sensitivity and device noise analysis based on physical models are shown to have a common background, since they amount to evaluating the small-signal device response to an impressed, distributed current source. This problem is addressed by means of a Green's function technique akin to Shockley's impedance field method. To allow the efficient numerical evaluation of the Green's function within the framework of a discretized physical model, inter-reciprocity concepts, based on the introduction of an adjoint device, are exploited. Examples of implementation involving GaAs MESFETs are discussed.>

A direct drive variable reluctance motor for robotic applications is considered. A cascade control structure is adopted, with an inner torque loop and an outer velocity loop. The inner loop consists of a static torque precompensator transforming the torque control problem into a current or flux control one. Optimization techniques that minimize power dissipation under the voltage limit imposed by the power amplifier are used to define an optimal ripple-free flux profile. Sliding mode implementation of the inner controller is considered, while the outer loop is designed using binary control techniques to achieve insensitivity to load and inertia variations. The drive is simulated for a single-link robotic arm, showing good performances in terms of residual torque ripple and velocity-tracking capability.>