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linear algebra 入门简介，mit的资料。
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linear algebra 入门简介，mit的资料。

Chapter 1 introduces the basic components of a distribution system. Included is an introduction to the type of data that is necessary to model a distribution system. Chapter 2 is a discussion of “load.” The attempt here is to make the student understand that the load on a distribution system is constantly changing, and that this must be taken into account in all studies. Chapter 3 presents some helpful approximate analysis techniques that will help the student know what “ballpark” answers to look for when more precise studies are made. Chapter 4 is a very important chapter in developing the exact model of line segments. How to take into account the unbalanced loading and unsymmetrical configurations in the calculation of line impedances is presented in great detail. Both overhead and underground lines are included. Chapter 5 is in many ways a continuation of Chapter 4, except that it is limited to shunt admittance calculations. Chapter 6 develops the first of the generalized matrices that will be used to model the major components of a distribution system. This chapter is limited to the three-phase, unbalanced line model. Chapter 7 addresses voltage regulation. Starting with a review of basic transformer theory, the chapter moves to the development of three-phase models of step-voltage regulators and their control. The models developed are in the form of generalized matrices similar to those developed for line segments. Chapter 8 develops comprehensive models of several of the standard three-phase transformer connections that are common on a distribution system. The models, again, are in the form of generalized matrices. Chapter 9 develops the models for the various types of loads on a distribution system. Chapter 10 puts it all together. All of the component models developed in earlier chapters are put together to form a model of a distribution feeder. The ladder iterative technique is developed and demonstrated. Also, the three-phase model for short-circuit studies is developed and demonstrated.

Programming MATLAB for Numerical Analysis introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. You will first become familiar with the MATLAB environment, and then you will begin to harness the power of MATLAB. You will learn the MATLAB language, starting with an introduction to variables, and how to manipulate numbers, vectors, matrices, arrays and character strings. You will learn about MATLAB's high-precision capabilities, and how you can use MATLAB to solve problems, making use of arithmetic, relational and logical operators in combination with the common functions and operations of real and complex analysis and linear algebra.

Use Python’s built-in features to create innovative graphics for data visualization and technical illustrations. This book goes beyond simple commands and libraries to explain how to not only display but also rotate, shade, and edit graphics for any purpose. Starting with the essential Python functions to set up a plotting space and produce 2 and 3-dimensional objects, you’ll learn how to construct more complex objects, translate and rotate them, remove hidden lines, introduce shading to add realism, and project images to visualize any dataset. The final chapter includes several worked applications in science and engineering including planetary models, which you can adapt for your own use. Written for developers who want to harness Python’s capabilities to fine-tune their images, Python Graphics covers the different commands for plotting dots, lines, arrows, or arcs, creating custom plotting grids, correcting distortions, adding text and labels to illustrations, manipulating arcs and circles, specify and use colors, and more. Armed with these techniques and core math skills, you’ll be ready to create and customize detailed technical illustrations or data visualizations. What You’ll Learn Use Python′s built-in commands for plotting, removing distortions, and rotating objects Create and edit 2D and 3D objects Develop illustrations for scientific and engineering applications Who This Book Is For Python developers looking for tips on how to create illustrations and visualizations, as well as scientists, engineers, or students using Python. It assumes familiarity with vectors, matrices, geometry and trigonometry.

C----------------------------------------------------------------------- program runocc C----------------------------------------------------------------------- c C OCCAM 2.0: Steven Constable IGPP/SIO La Jolla CA 92093-0225 c Program Revision 2.01, 13 Jan 1993 c c runocc is the calling program for OCCAM v2.0. C C REFERENCES: CONSTABLE, PARKER & CONSTABLE, 1987: GEOPHYSICS 52, 289-300. C DEGROOT-HEDLIN & CONSTABLE, 1990: GEOPHYSICS 55, 1613-1624. C CONSTABLE, 1991: GEOPHYS. J. INT. 106, 387-388. C CONSTABLE, 1992: OCCAM DISTRIBUTION NOTES. C C REVISION HISTORY: C MARCH 1986, (VERSION 1.2) C OCTOBER 1987, (VERSION 1.3) C AUGUST 1988, (VERSION 1.4) C JANUARY 1989 (WITH THANKS TO C.DEGROOT-HEDLIN), (VERSION 1.5) C SEPTEMBER 1989, (VERSION 1.5.2) C APRIL 1992 (MORE THANKS TO CATHERINE AND ALSO WSE) (VERSION 2.0) C C IF YOU OBTAIN THIS CODE FROM A THIRD PERSON, PLEASE SEND YOUR NAME AND ADDRESS C TO S. CONSTABLE. YOU WILL THEN RECEIVE UPDATES, NEWS ON BUGS, ETC. C C VERSION 2.0 IS A RE-WRITE TO MAKE OCCAM INDEPENDENT OF THE DIMENSIONALITY C OF THE FORWARD PROBLEM, AND TO MAKE MAXIMUM USE OF DYNAMIC MEMORY ALLOCATION, C AS THE ARRAY SIZES FOR THE 2D PROBLEM ARE NOW GETTING TOO LARGE FOR COMFORT. C INCLUDE FILES ARE NOW USED TO STREAMLINE CHANGES OF DIMENSION. C IMPLICIT DOUBLE PRECISION HAS BEEN REMOVED, AGAIN FOR STORAGE REASONS. C CALLING PROGRAM IS NOW AN INTEGRAL PART OF THE PACKAGE AS ALL THE MODEL- C DEPENDENT STUFF HAS BEEN SPUN OFF. C C IF YOU OBTAIN THIS CODE FROM A THIRD PERSON, PLEASE SEND YOUR NAME AND ADDRESS C TO S. CONSTABLE. YOU WILL THEN RECEIVE UPDATES, NEWS ON BUGS, ETC. C C SUBROUTINES WHICH MUST BE SUPPLIED BY THE USER: C C FORMOD(NP,ND,PM,DP,DM), COMPUTES THE FORWARD FUNCTION FOR MODEL PM() AT C THE DATA PARAMETERS DP() AN

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