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.
Efficient implementation of the activation function is important in the hardware design of artificial neural networks. Sigmoid, and hyperbolic tangent sigmoid functions are the most widely used activation functions for this purpose. In this paper, we present a simple and efficient architecture for digital hardware implementation of the hyperbolic tangent sigmoid function. The proposed method employs...
The hyperbolic tangent function is commonly used as the activation function in artificial neural networks. In this work two different hardware implementations for the hyperbolic tangent function are proposed. Both methods are based on the approximation of the function rather than calculating it, since it has exponential nature. The first method uses a lookup table to approximate the function, while...
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.