Jaypee Institute of Information Technology

About: Jaypee Institute of Information Technology is a education organization based out in Noida, Uttar Pradesh, India. It is known for research contribution in the topics: Computer science & Cluster analysis. The organization has 2136 authors who have published 3435 publications receiving 31458 citations. The organization is also known as: JIIT Noida.

A speed based adaptive algorithm for reducing paging cost in cellular networks

Abstract: Location update and paging are important parts of location management of cellular network. This paper deals with a new algorithm to reduce paging cost using speed adaptive strategy. The proposed algorithm uses speed distribution and random walk model to develop look-up tables for mobile terminal. These tables are used to find out subarea size to be paged. Paging area is further reduced by introduction of 120 degree paging zones. A paging agent is used to store previous VLR address and helps to find out optimal paging zone. The proposed algorithm is capable of reducing the paging cost approximately by a factor of two for maximum subarea area size 6 i.e. approximately half of the cells are required to be paged.

A Stacked Technique for Gender Recognition Through Voice

Abstract: Detecting the gender of a person (male or female) through their voice seems to be a very trivial task for humans. Our minds are trained over the course of time to detect the differences in voices of males and females. Our ears work as the front end, receiving the audio signals which our brain processes and makes the decision. But it is a challenging problem for computers. Gender classification has applications like, it is able to improve the intelligence of a surveillance system, analyze the customer's demands for store management, and allow the robots to perceive gender etc. This paper proposes a stacked machine learning algorithm to determine gender using the acoustic parameters of voice sample and compares its performance with existing classifiers as CART, Random forest and neural network.

An adaptive notch filter for narrow band interference removal

Abstract: A modification on an existing algorithm to dynamically adapt to interfering signal frequency and its magnitude is given. The algorithm first detects the presence of the interfering signal in real time and if present, it adjusts parameters to maximize the signal to noise ratio at the output. The AWGN and interfering signal power is taken in a wide dynamic range - up to 20 dB and 80 dB respectively. The proposed IIR filter detects and almost perfectly removes the interference.