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Jayasri, T.
- Categorization of Respiratory Signal using ANN and SVM based on Feature Extraction Algorithm
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Authors
T. Jayasri
1,
M. Hemalatha
2
Affiliations
1 Embedded Systems, School of Computing, SASTRA University, Thanjavur, TamilNadu,, IN
2 School of Computing, SASTRA University, Thanjavur, TamilNadu, IN
1 Embedded Systems, School of Computing, SASTRA University, Thanjavur, TamilNadu,, IN
2 School of Computing, SASTRA University, Thanjavur, TamilNadu, IN
Source
Indian Journal of Science and Technology, Vol 6, No 9 (2013), Pagination: 5195-5200Abstract
Sleep apnea is a dishevelment that causes interruption in breath or shoal of the respiration. The respiratory signal is classified into three states such as normal respiration, motion artifacts, and sleep apnea and it is obtained from a physionet. Firstly, using a second order auto regressive modeling, an algorithm is developed to attain the energy and frequency parameters of the signal and then the signal is classified with threshold based manual classification into any of the above taxonomy. In addition to this dataset, MLP is trained with a back propagation learning algorithm that results in reduced time, iterations and errors. Consequently, the training of SVM, a binary classifier used to solve multiple class problems is done with the same data set and classification is made to reduce overall errors. The overall efficiency of the above techniques is compared.Keywords
Feature Extraction, Autoregressive Model, Burgs Method, Multilayer Perceptron, Back Propagation Learning Algorithm, Support Vector MachineFull Text
References
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- Path Loss Prediction in Wireless Communication System Using Fuzzy Logic
Abstract Views :236 |
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Authors
Affiliations
1 School Of Computing, SASTRA University, Thanjavur, Tamil Nadu, IN
1 School Of Computing, SASTRA University, Thanjavur, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 7, No 5 (2014), Pagination: 642-647Abstract
The portable wireless technology with wide accessibility facilitates the people to enter into a new dynamic environment for optimizing the overall productivity. Establishing reliable communication is a challenging aspect, because the signal propagation is heavily subjected to interference and fading effects resulting in severe path loss. In the field of telecommunication system, the effect of Path Loss in the signal is used to analyze and design the link budget system. Previously, many path loss prediction models like HATA, and Okumura are proposed where the path loss is determined with the help of experimental field values and verified with the help of the model graph. In this work, BPSK modulated signal is used to determine the path loss using HATA empirical formula derived with the help of the Okumura curve for various urban, suburban and rural areas. The identified values are given to triangular membership function and defuzzification is performed using faster and flexible center of sum method. The inferred results show maximum loss in case of urban and increases at an average rate of 10dB per decade with distance. The proposed technique optimizes signal transmission by determining the path loss accurately.Keywords
Binary Phase Shift Keying, Fuzzy Logic, HATA Model, Okumura Model, Path LossaFull Text