Hyperspectral Imaging: Techniques for Spectral Detection and Classification is an outgrowth of the research conducted over the years in the Remote Sensing Signal and Image Processing Laboratory (RSSIPL) at the University of Maryland, Baltimore County. It explores applications of statistical signal processing to hyperspectral...
This book concerns testing hypotheses in non-parametric models. Generalizations of many non-parametric tests to the case of censored and truncated data are considered. Most of the test results are proved and real applications are illustrated using examples. Theories and exercises are provided. The incorrect use of many tests applying most...
With a foreword by Paul M. Churchland and Patricia S. ChurchlandThis book represents the views of one of the greatest mathematicians of the twentieth century on the analogies between computing machines and the living human brain. John von Neumann concludes that the brain operates in part digitally, in part analogically, but uses a peculiar...
In the early days of pattern recognition and statistical data analysis life was
rather simple: datasets were relatively small, collected from well-designed experiments,
analyzed using a few methods that had good theoretical background.
Explosive growth of the use of computers led to the creation of huge amounts of
data of all kinds,...
Uncover hidden patterns of data and respond with countermeasures
Security professionals need all the tools at their disposal to increase their visibility in order to prevent security breaches and attacks. This careful guide explores two of the most powerful ? data analysis and visualization. You'll soon understand how to...
There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled “DATA MINING: Foundations and Intelligent Paradigms: Volume 2: Core Topics including Statistical, Time-Series and Bayesian Analysis” we wish to introduce some of the latest developments to a broad audience of...
Student-Friendly Coverage of Probability, Statistical Methods, Simulation, and Modeling Tools
Incorporating feedback from instructors and researchers who used the previous edition, Probability and Statistics for Computer Scientists, Second Edition helps students understand general methods of stochastic...
Nowadays data accumulate at an alarming speed in various storage devices, and so does valuable information. However, it is difficult to understand information hidden in data without the aid of data analysis techniques, which has provoked extensive interest in developing a field separate from machine learning. This new field is...
In this publication, the author Kristian Kersting has made an assault on one of the hardest integration problems at the heart of Artificial Intelligence research. This involves taking three disparate major areas of research and attempting a fusion among them. The three areas are: Logic Programming, Uncertainty Reasoning and Machine Learning. Every...
Data mining and data modeling are hot topics and are under fast development. Because of its wide applications and rich research contents, a lot of practitioners and academics are attracted to work on these areas. In the view of promoting the communications and collaborations among the practitioners and researchers in Hong Kong, a two-day...
You have a mound of data sitting in front of you and a suite of computation tools at your disposal. And yet, you’re stumped as to how to turn that data into insight. Which part of that data actually matters, and where is this insight hidden?
If you’re a data scientist who struggles to navigate the murky space...
