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.
Single-layer feedforward networks (SLFNs) have been proven to be a universal approximator when all the parameters are allowed to be adjustable. It is widely used in classification and regression problems. The SLFN learning involves two tasks: determining network size and training the parameters. Most current algorithms could not be satisfactory to both sides. Some algorithms focused on construction...
By introducing an extra dimension to the inputs, sigmoid function can simulate the behavior of traditional RBF units. This paper introduces a sigmoid based RBF neuron and compares it with traditional RBF neuron. Neural networks composed of these neurons are trained with ErrCor algorithm on two classic experiments. Comparison results are presented to show advantages of the sigmoid based RBF model.
A new density- and grid-based clustering algorithm is proposed to identifying free shape clusters. The proposed algorithm is a non-parametric method, which does not require user specifying parameters for clustering. The algorithm divides each dimension of the data space into certain intervals to form a grid structure. The valley seeking procedure is employed to find the cluster centers where the data...
The Detection and analysis of neural spike activity is a prerequisite for studying many types of brain functions. In this paper, we introduce an open source toolbox built in MATLAB called SPKtool for spike analysis. SPKtool functions support common requirement for analysis of neural spikes, including spike detection, feature extraction, manual and semi-automatic clustering methods and graphical tools...
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.