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These lectures give an elementary introduction to the important recent developments of the applications of N=1 supergravity to the construction of unified models of elementary particle interactions. Topics covered include couplings of supergravity with matter, spontaneous symmetry breaking and the super-higgs effect, construction of supergravity unified models, and the phenomenon of SU(2) x U(1) electroweak-symmetry breaking by supergravity. Experimental consequences of N-1 supergravity unified theory, in particular, the possible supersymmetric decays of the W± and Z0 bosons, are also discussed. The treatment presented encompasses a broad class of models, both of the tree breaking as well as the radiative breaking of SU(2) x U(1). Rules of tensor calculus and the explicit construction of the Lagrangian of the Supergravity-matter couplings are given in the appendix.
"A valuable reference." — American Scientist. Excellent graduate-level treatment of set theory, algebra and analysis for applications in engineering and science. Fundamentals, algebraic structures, vector spaces and linear transformations, metric spaces, normed spaces and inner product spaces, linear operators, more. A generous number of exercises have been integrated into the text. 1981 edition.
The second edition of this book would not have been possible without the comments and suggestions from students, especially those at Columbia University. Many of the new topics introduced here are a direct result of student feedback that helped refine and clarify the material. The intention of this book was to develop material that the author would have liked to have had available as a student. Theory of Applied Robotics: Kinematics, Dynamics, and Control (2nd Edition) explains robotics concepts in detail, concentrating on their practical use. Related theorems and formal proofs are provided, as are real-life applications. The second edition includes updated and expanded exercise sets and problems. New coverage includes: components and mechanisms of a robotic system with actuators, sensors and controllers, along with updated and expanded material on kinematics. New coverage is also provided in sensing and control including position sensors, speed sensors and acceleration sensors. Students, researchers, and practicing engineers alike will appreciate this user-friendly presentation of a wealth of robotics topics, most notably orientation, velocity, and forward kinematics.
These lectures give an elementary introduction to the important recent developments of the applications of N=1 supergravity to the construction of unified models of elementary particle interactions. Topics covered include couplings of supergravity with matter, spontaneous symmetry breaking and the super-higgs effect, construction of supergravity unified models, and the phenomenon of SU(2) x U(1) electroweak-symmetry breaking by supergravity. Experimental consequences of N-1 supergravity unified theory, in particular, the possible supersymmetric decays of the W± and Z0 bosons, are also discussed. The treatment presented encompasses a broad class of models, both of the tree breaking as well as the radiative breaking of SU(2) x U(1). Rules of tensor calculus and the explicit construction of the Lagrangian of the Supergravity-matter couplings are given in the appendix.
An outstanding introduction to the fundamentals of regression analysis-updated and expanded The methods of regression analysis are the most widely used statistical tools for discovering the relationships among variables. This classic text, with its emphasis on clear, thorough presentation of concepts and applications, offers a complete, easily accessible introduction to the fundamentals of regression analysis. Assuming only a basic knowledge of elementary statistics, Applied Regression Analysis, Third Edition focuses on the fitting and checking of both linear and nonlinear regression models, using small and large data sets, with pocket calculators or computers. This Third Edition features separate chapters on multicollinearity, generalized linear models, mixture ingredients, geometry of regression, robust regression, and resampling procedures. Extensive support materials include sets of carefully designed exercises with full or partial solutions and a series of true/false questions with answers. All data sets used in both the text and the exercises can be found on the companion disk at the back of the book. For analysts, researchers, and students in university, industrial, and government courses on regression, this text is an excellent introduction to the subject and an efficient means of learning how to use a valuable analytical tool. It will also prove an invaluable reference resource for applied scientists and statisticians.
Since the publication of the first edition of this book, the area of mathematical finance has grown rapidly, with financial analysts using more sophisticated mathematical concepts, such as stochastic integration, to describe the behavior of markets and to derive computing methods. Maintaining the lucid style of its popular predecessor, this concise and accessible introduction covers the probabilistic techniques required to understand the most widely used financial models. Along with additional exercises, this edition presents fully updated material on stochastic volatility models and option pricing as well as a new chapter on credit risk modeling. It contains many numerical experiments and real-world examples taken from the authors' own experiences. The book also provides all of the necessary stochastic calculus theory and implements some of the algorithms using SciLab. Key topics covered include martingales, arbitrage, option pricing, and the Black-Scholes model.