121 research outputs found
Understanding a philosophical text. The problem of “meaning” in Jayanta’s Nyāyamañjarī, Book 5
No full textThe authors make an attempt to comparatively analyse some stances of the Old Indian philosophy of language, exemplified by the Medieval Indian author Jayanta, along with the Western tradition of the analytical philosophy of language, and to highlight the differences as well as the similarities
Online Adaptive Hierarchical Clustering in a Decision Tree Framework
No full textOnline clustering is an issue in large amount of data crunching. Moreover, having a coarse-to-fine grain analysis is also desirable. We address both these problems in a single framework by designing an online adaptive hierarchical clustering algorithm in a decision tree framework. Our model consists of an online adaptive binary tree and a code formation layer. The adaptive tree hierarchically partitions the data and the finest level clusters are represented by the leaf nodes. The code formation layer stores the representative codes of the clusters corresponding to the leaf nodes, and the tree adapts the separating hyperplanes between the clusters at every layer in an online adaptive mode. The membership of a sample in a cluster is decided by the tree and the tree parameters are guided by the stored codes. As opposed to the existing hierarchical clustering techniques where certain local objective function at every level is optimized, we adapt the tree in an online adaptive mode by minimizing a global objective functional. We use the same global objective functional as used in the fuzzy c-means algorithm (FCM), however, we observe that the effect of the control parameter is different from that in the FCM. In our model the control parameter regulates the size and the number of clusters whereas in the FCM the number of clusters is always constant (c). We never freeze the adaptation process. For every input sample, the tree allocates it to certain leaf node and at the same time adapts the tree parameters simultaneously with the adaptation of the stored codes. We validate the effectiveness of our model on certain real-life datasets and also show that the model is able to perform unsupervised classification on certain datasets
Dynamical response of an excitatory-inhibitory neural network to external stimulation: An application to image segmentation
No full textNeural network models comprising elements that have exclusively excitatory or inhibitory synapses are capable of a wide range of dynamical behavior, including chaos. In this paper, a simple excitatory-inhibitory neural pair, which forms the building block of larger networks, is subjected to external stimulation. The response shows transition between various types of dynamics, depending upon the magnitude of the stimulus.
The corresponding network model, obtained by coupling such pairs over a local neighborhood in a twodimensional plane, can achieve a satisfactory segmentation of an image into ‘‘object’’ and ‘‘background.’’ Results for synthetic and ‘‘real-life’’ images are given
Dynamics of Labour Force for Human Resource Management: A Local Economy Perspective in Bangladesh
No full textResponse of an Excitatory-Inhibitory Neural Network to External Stimulation: An Application to Image Segmentation
No full textNeural network models comprising elements which have exclusively excitatory or inhibitory synapses are capable of a wide range of dynamic behavior, including chaos. In this paper, a simple excitatory-inhibitory neural pair, which forms the building block of larger networks, is subjected to external stimulation. The response shows transition between various types of dynamics, depending upon the magnitude of the stimulus. Coupling such pairs over a local neighborhood in a two-dimensional plane, the resultant network can achieve a satisfactory segmentation of an image into "object" and "background"
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