The Padmakar-Ivan (PI) index is a first-generation topological index (TI) based on sums over all edges between numbers of edges closer to one endpoint and numbers of edges closer to the other endpoint. Edges at equal distances from the two endpoints are ignored. An analogous definition is valid for the Wiener index W, with the difference that sums are replaced by products. A few other TIs are d...

Endpoint results are presented for multi-valued cyclic contraction mappings on complete metric spaces (X, d). Our results extend previous results given by Nadler (1969), Daffer-Kaneko (1995), Harandi (2010), Moradi and Kojasteh (2012) and Karapinar (2011).

This paper addresses the problem of audio change detection and speaker tracking in broadcast TV streams. A two-pass audio change detection algorithm, which includes detection of the potential change boundaries and refinement, is proposed. Speaker tracking is performed based on the results of speaker change detection. In speaker tracking, Wiener filtering, endpoint detection of pitch, and segmen...

It is very important to detect the speech endpoints accurately in speech recognition. This paper presents a comparative analysis of various feature extraction techniques of endpoint detection in speech recognition of isolated words in noisy environments. The endpoint detection problem is nontrivial for no stationary backgrounds where artifacts (i.e., no speech events) may be introduced by the s...

In this paper we propose an endpoint detection system based on the use of several features extracted from each speech frame, followed by a robust classifier (i.e Adaboost and Bagging of decision trees, and a multilayer perceptron) and a finite state automata (FSA). We present results for four different classifiers. The FSA module consisted of a 4-state decision logic that filtered false alarms ...

In this paper, we describe a new speech/non-speech classification method that improves the endpoint detection performance for speech recognition in noisy environments. The proposed method uses multiple features to increase the robustness in noisy environments, and the classification and regression tree(CART) technique is applied to effectively combine these multiple features for classification ...

In the analysis of nonlinear, non-stationary signal is better than the traditional wavelet signal analysis method, commonly used in this kind of signal singular value point detection. Empirical mode decomposition (EMD) is the core of the analysis method, but EMD in the original HHT method exists end effect in decomposition process, the decomposition of intrinsic mode functions IMF serious disto...