Ross's classic bestseller, Introduction to Probability Models, has been used extensively by professionals and as the primary text for a first undergraduate course in applied probability. It provides an introduction to elementary probability theory a
Section 1 Introduction Chapter 1 What are Gene Regulatory Networks? ................................................................................................... 1 Alberto de la Fuente, CRS4 Bioinformatica, Italy Chapter 2 Introduction to GRNs
CONTENTS Contents v Preface to the Second Edition xv Preface to the First Edition xvii Acknowledgments for the Second Edition xxi Acknowledgments for the First Edition xxiii 1 Introduction and Preview 1.1 Preview of the Book 2 Entropy, Relative Entr
Jim Kurose Jim Kurose is a Distinguished University Professor of Computer Science at the University of Massachusetts, Amherst. Dr. Kurose has received a number of recognitions for his educational activities including Outstanding Teacher Awards from
This text is intended as an introduction to elementary probability theory and stochastic processes. It is particularly well suited for those wanting to see how probability theory can be applied to the study of phenomena in fields such as engineering
Preface ix Chapter 1 Introduction to Design 1 1.1 The Design Process 2 1.2 Engineering Design versus Engineering Analysis 4 1.3 Conventional versus Optimum Design Process 4 1.4 Optimum Design versus Optimal Control 6 1.5 Basic Terminology and Notati
# Machine learning algorithms A collection of minimal and clean implementations of machine learning algorithms. ### Why? This project is targeting people who want to learn internals of ml algorithms or implement them from scratch. The code is much e
This, Reader, is an honest book. It warns you at the outset that it is not a treatise on stochastic volatility. Nor is it a mathematical nance textbook – there are treatises and textbooks galore on the shelves of bookshops and university libraries.
Soft computing and nature-inspired computing both play a significant role in developing a better understanding to machine learning. When studied together, they can offer new perspectives on the learning process of machines. The Handbook of Research
The Applied and Numerical Harmonic Analysis (ANHA) book series aims to provide the engineering, mathematical, and scientific communities with significant developments in harmonic analysis, ranging from abstract harmonic analysis to basic application
This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of
Suitable for a first year graduate course, this textbook unites the applications of numerical mathematics and scientific computing to the practice of chemical engineering. Written in a pedagogic style, the book describes basic linear and nonlinear al
这是一个随机几何模型的一次实现作图，模拟一个蜂窝网络中H2H（人与人通信）与MTC（机器类通信）用户共存的异构网络，以基站为圆心，r_BS为半径的圆形二维区域中，H2H用户在空间的分布服从强度为lamda_H的泊松点过程（Poisson Point Process，简称PPP），MTC用户采用数据聚合的方式，即
MTC设备（MTCD）的数据发送到数据聚合器（aggregator），这种发送方式可以参见论文Aggregation and Resource Scheduling in Machine
The problem of mean square exponential stability for a class of impulsive stochastic fuzzy Cohen–Grossberg networks with mixed delays and reaction–diffusion terms is investigated in this paper. By using the properties of ‘‘M-c
