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In this paper we present an online handwritten symbol recognition system for Telugu, a widely spoken language in India. The system is based on Hidden Markov Models (HMM) and uses a combination of time-domain and frequency-domain features. The system gives top-1 accuracy of 91.6% and top-5 accuracy of 98.7% on a dataset containing 29,158 train samples and(More)
local feature, DTW, hand writing recognition This paper describes character based elastic matching using local features for recognizing online handwritten data. Dynamic Time Warping (DTW) has been used with four different feature sets: x-y features, Shape Context (SC) and Tangent Angle (TA) features, Generalized Shape Context feature (GSC) and the fourth(More)
Spectral Clustering is a graph theoretic technique to find groupings within the data. Mostly all the users will choose K-means clustering algorithm to finding the groups as it is easy to implement. To apply K-means algorithm user has to specify the value of K(number of clusters). It is very difficult to navie users to supply K value as they are not having(More)
A Mobile Ad-Hoc Network (MANET) represents a system of wireless mobile nodes that can freely and dynamically self organize into arbitrary and temporary network topologies without presence of any fixed infrastructure. Multicast routing in MANETs is an efficient method to lead data packets from one source group to several nodes as destination group.(More)
The IEEE802.11a standard uses Orthogonal Frequency Division Multiplexing (OFDM). It can provide data rate up to 54 Mbps in Wireless Local Area Networks (WLAN's). This standard is used in indoor applications as well as in vehicles i.e. mobile environments. In this paper, we evaluate Bit Error Rate (BER) by changing the number of pilots using multiple(More)
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