AN FPGA IMPLEMENTATION OF DS-SS COMMUNICATION SYSTEM USING PSEUDO CHAOTIC SEQUENCE GENERATOR
Published In: INTERNATIONAL CONFERENCE ON RECENT TRENDS IN COMPUTING AND COMMUNICATION ENGINEERING
Author(s): AMIT TRIPATHI , RAHUL NAWKHARE
Abstract: Chaotic system are unstable and a-periodic ,making them naturally difficult to identify and to predict .This nonlinear , unstable and a-periodic characteristics of chaotic signals has numerous features that make it attractive for communication use. This field of communication is termed as chaotic communication. Chaotic communication signals have large bandwidth and have low power spectrum density. In chaotic communication, the digital information to be transmitted is placed directly onto a wide band chaotic signal. Spread spectrum is a means of transmission, in which signal occupies bandwidth much more than the one necessary to send the information, the band spread is accomplished by utilizing a code which is independent of data. In this paper an attempt has been made to proposed and analysed the spread spectrum along with the performance analysed of pseudo chaotic code generator implemented in spread spectrum communication system. The sequence generator and the DS-SS for single user a
- Publication Date: 21-Apr-2013
- DOI: 10.15224/978-981-07-6184-4-49
- Views: 0
- Downloads: 0
FISH STOCK PREDICTION USING DATA MINING AND IMAGE PROCESSING TECHNIQUES BASED ON SALINITY, TEMPERATURE AND CHLOROPHYLL DISTRIBUTION
Published In: INTERNATIONAL CONFERENCE ON RECENT TRENDS IN COMPUTING AND COMMUNICATION ENGINEERING
Author(s): MADANA MOHANA R , PRUDHVI KUMAR REDDY K , RAMA MOHANA REDDY A
Abstract: Agriculture is the main occupation of the people who are living in most of the developing and under developed countries. And People also depending on fish production for their livelihood. Fish stock estimation has been put forth by Marine societies, using the images sent by the satellites. But, this estimation sometimes fails due to the sudden changes in climatic conditions. The present paper has addressed the above problem. The main object of this paper is to predict the stock concentration with high accuracy rate. This paper mainly uses the concepts of image processing, data mining and strives for the development of a high accurate model. As the number of parameters has been increased, the accuracy of the model will be increased. The aim is to predict the correct geographical position of the fish stock concentration and will extended for several additional inclusions such as prediction of accurate fish number and type of fish etc.
- Publication Date: 21-Apr-2013
- DOI: 10.15224/978-981-07-6184-4-50
- Views: 0
- Downloads: 0