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- K. Rajeswari, Tresa Sangeetha, A.P Natchammai, Mrs. J. Nandhini, S. J. Thiruvengadam
- 2010 5th International Conference on Industrialâ€¦
- 2010

This paper deals with the performance analysis of channel estimation methods for LTE downlink system over time varying mobile environments. The analysis of channel estimation in the presence of interference is also done. Least square frequency domain (LS_Freq), least square time domain (LS_Time), maximum likelihood (ML) and minimum mean square errorâ€¦ (More)

In this paper different classification techniques of Data Mining are compared using diverse datasets from University of California, Irvine(UCI). Accuracy and time required for execution by each technique is observed. The Data Mining refers to extracting or mining knowledge from huge volume of data. Classification is an important data mining technique withâ€¦ (More)

K. Rajeswari , Dr. V. Vaithiyanathan , Dr.P. Amirtharaj 3 1 Research Scholar, Department of Information Technology, School of Computing, SASTRA University, Tanjore, India. raji.pccoe@gmail.com 2 Professor, Department of Information Technology, School of Computing, SASTRA University, Tanjore, TamilNadu, India. Assistant Professor, Department of Cardioâ€¦ (More)

- K. Rajeswari, V. Vaithiyanathan, +12 authors Vipin Kumar
- 2012

Data mining is a field which searches for interesting knowledge or information from existing massive collection of data. In particular, algorithms like Apriori help a researcher to understand the potential knowledge, deep inside the data base. But due to the large time consumed by Apriori to find the frequent item sets and generate rules, severalâ€¦ (More)

- Payal P. Dhakate, Payal P.Dhakate, Suvarna Mahavir Patil, K. Rajeswari, Deepa Abin
- 2014

Data mining is a process of extracting information from a dataset and transform it into understandable structure for further use, also it discovers patterns in large data sets [1]. Data mining has number of important techniques such as preprocessing, classification. Classification is one such technique which is based on supervised learning. It is aâ€¦ (More)

- V. Vaithiyanathan, K. Rajeswari, Rashmi Phalnikar, Swati Tonge
- 2012 IEEE International Conference onâ€¦
- 2012

Association rule mining is used to uncover closely related item sets in transactions for deciding business policies. Apriori algorithm is widely adopted is association rule mining for generating closely related item sets. Traditional apriori algorithm is space and time consuming since it requires repeated scanning of whole transaction database. In thisâ€¦ (More)

Fuzzy logic has proved in this paper, a medical fuzzy data is introduced in order to help users in providing accurate information when there is inaccuracy. Inaccuracy in data represents imprecise or vague values (like the words use in human conversation) or uncertainty in using the available information required for decision making handle the uncertainty ofâ€¦ (More)

- K. Rajeswari, Omkar Acharya, Mayur Sharma, Mahesh Kopnar, Kiran Karandikar
- 2015 International Conference on Computingâ€¦
- 2015

The set of objects having same characteristics are organized in groups and clusters of these objects reformed known as Data Clustering. It is an unsupervised learning technique for classification of data. K-means algorithm is widely used and famous algorithm for analysis of clusters. In this algorithm, n number of data points are divided into k clustersâ€¦ (More)

- S. Thenmozhi, K. Rajeswari
- IEEE-International Conference On Advances Inâ€¦
- 2012

Kalman estimator is designed to estimate the unmeasurable system states in an Active Suspension System (ASS) in two modes. In the first mode, the estimated road input is given to the estimator to estimate the state variables. In the second mode, the actual road input is given to the estimator to estimate the state variables. In both the modes, the estimatedâ€¦ (More)

Attribute selection also called as feature selection is a preprocessing technique to select a set of features or subset of features from the available large collection of features. An artificial neural network is the simulation of a human brain which learns with experience. Efficiency of a model or a system in terms of cost, time and accuracy will greatlyâ€¦ (More)