IDR-QR: Incremental Dimension Reduction Algorithm via QR Decomposition (Java)
IEE Transactions on Knowledge and Data Engineering, Vol. 17, No. 9,

Abstract:
Dimension reduction is a critical data preprocessing step for many database and data mining applications, such as efficient storage and retrieval of high-dimensional data. In the literature, a well-known dimension reduction algorithm is Linear Discriminant Analysis (LDA). The common aspect of previously proposed LDA-based algorithms is the use of Singular Value Decomposition (S ....etc

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Abstract Dimensionality reduction is an important step in knowledge discovery in databases. Intrinsic dimension indicates the number of variables necessary to describe a data set. Two methods, box-counting dimension and correlation dimension, are commonly used for intrinsic dimension estimation. However, the robustness of these two methods has not been rigorously studied. This paper demonstrates that correlation dimension is more robust with respect to data sample size. In addition, instead of using a user selected distance , we propose a new ....etc

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Why Use Hyperspectral Imagery



Introduction

While multispectral images have

been in regular use since the 1970s,

the widespread use of hyperspectral

images is a relatively recent trend.

Hyperspectral imaging, also known as im-

aging spectrometry, is now a reasonably fa-

Wmiliar concept in the world of remote sensing.

However, for many remote sensing specialists who

have not yet had the opportunity to use hyperspectral imagery in ....etc

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To get full information or details of dimension reduction in hyperspectral image matlab code please have a look on the pages

http://seminarsprojects.net/Thread-why-use-hyperspectral-imagery

http://seminarsprojects.net/Thread-towards-real-time-compression-of-hyperspectral-images-using-virtex-ii-fpgas

if you again feel trouble on dimension reduction in hyperspectral image matlab code please reply in that page and ask specific fields ....etc

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Towards Real-Time Compression of Hyperspectral Images Using Virtex-II FPGAs
Antonio Plaza
Department of Computer Science, University of Extremadura
Avda. de la Universidad s/n, E-10071 Caceres, Spain


Abstract.
Hyperspectral imagery is a new type of high-dimensional image data which is now used in many Earth-based and planetary exploration applications. Many efforts have been devoted to designing and developing compression algorithms for hyperspectral imagery. Unfortunately, most availab ....etc

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Send me information regarding this topic (( new dimension of data security using neural networks and numerical functions)) ....etc

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Abstract:
Intel announced a new brand name for its next generation mobile processor technology: Centrino. It was designed to help manufactures to build notebooks that use less power and offer extended battery life along with better wireless networking facilities.

CONTENT
Introduction
Users demand
Notebook PCs: Two Distinct Segments
Configuration
Intel Centrino Mobile Technology
New Centrino technology
Key feature of Intel centrino mobile technology ....etc

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gabor matlab code for hyperspectral image

Abstract

Sparse-representation-based classification (SRC) assigns a test sample to the class with minimum representation error via a sparse linear combination of all the training samples, which has successfully been applied to several pattern recognition problems. According to compressive sensing theory, the l1-norm minimization could yield the same sparse solution as the l0 norm under certain conditions. However, the computational complexity of the l1-norm optimization process is often too high for l ....etc

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HYPERSPECTRAL IMAGING


INTRODUCTION

With the advent of new technologies, the field of remote sensing too has gained a new height. Hyperspectral imaging collects and processes information from across electromagnetic spectrum. The most significant recent breakthrough in remote sensing has been the development of hyperspectral sensors and software to analyze the resulting image data. Fifteen years ago only spectral remote sensing experts had access to hyperspectral images or softwar ....etc

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