The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Retinal image is one of the robust and accurate biometrics which can be used to authenticate an individual. Feature matching is a key step for any biometric system and its implementation on hardware structures is often challenging due to the required object based processing. This paper presents an approach for retina tree biometric matching which has the capability to be implemented on a low power...
Multiplier circuits play an important role in reversible computation, which is helpful in diverse areas such as low power CMOS design, optical computing, DNA computing and bioinformatics, quantum computing and nanotechnology. In this paper a new reversible device called MFA (modified full adder) is used to design a novel reversible 4-bit binary multiplier circuit with low hardware complexity. It has...
Stereo vision based obstacle detection is an algorithm that aims to detect and compute obstacle depth using stereo matching and disparity map. This paper presents a robust method to detect positive obstacles including staircases in highly textured environments. The proposed method is easy to implement and fast enough for obstacle avoidance. This work is partly inspired by the work of Nicholas Molton...
Saturation conditions of the hidden layer neurons are a major cause of learning retardation in multilayer perceptrons (MLP). Under such conditions the traditional backpropagation (BP) algorithm is trapped in local minima. To renew the search for a global minimum, we need to detect the traps and an offset scheme to avoid them. We have discovered that the gradient norm drops to a very low value in local...
In this paper, we propose a MLP learning algorithm based on the parallel tangent gradient with modified variable learning rates, PTGVLR. Parallel tangent gradient uses parallel tangent deflecting direction instead of the momentum. Moreover, we use two separate and variable learning rates one for the gradient descent and the other for accelerating direction through parallel tangent. We test PTGVLR...
In this paper, an optimization method based on genetic algorithms (GA) is applied to find the best design parameters of the switching power circuit for a switched reluctance motor (SRM). The optimal parameters are found by GA with two objective functions, i.e. efficiency and torque ripple. A fuzzy expert system for predicting the performance of a switched reluctance motor has been developed. The design...
In gradient based learning algorithms, momentum usually has an improving effect on convergence rate and reduces zigzagging phenomena but sometimes it causes the convergence rate to decrease. The parallel tangent (partan) gradient is used as a deflecting method to improve the convergence. In this paper, we modify the gradient partan algorithm for learning the neural networks by using two different...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.