Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/14367
Title: Robust signal processing algorithms for detection of small targets in sea environment
Authors: RAMAN SUDHA
Keywords: Embedding, Lyapunov exponent, sea clutter, chaotic dynamics, Kernel independent component analysis, chaotic invariants, dynamic reconstruction.
Issue Date: 29-Oct-2004
Source: RAMAN SUDHA (2004-10-29). Robust signal processing algorithms for detection of small targets in sea environment. ScholarBank@NUS Repository.
Abstract: A robust scheme is introduced and analyzed for its performance to detect small targets in sea environment. This scheme includes the following special features:(i) The phase space of the system is extracted from the observed time series using embedding delay method, followed by Kernel Independent Component Analysis (KICA) algorithm as a feature selector. (ii) The prediction model is constructed using real time recurrent learning (RTRL) neural network.(iii) The stability is maintained in case of recursive prediction using the largest Lyapunov exponent of the system. The algorithms are studied in detail using Lorenz map and five different sea cutter time series datasets.
URI: http://scholarbank.nus.edu.sg/handle/10635/14367
Appears in Collections:Master's Theses (Open)

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