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Solution Manuals And Various Book Notes




Differential Equations by William E. Boyce and Richard DiPrima.
Calculus by William E. Boyce and Richard DiPrima.
The Calculus - A Genetic Approach by Otto Toeplitz.
Introduction to Calculus and Analysis by Richard Courant and Fritz John.
A Course of Modern Analysis by E. T. Whittaker and G. N. Watson.
Ordinary Differential Equations by Edward L. Ince.
Div, Grad, Curl, and All That: An Informal Text on Vector Calculus by H. M. Schey.
Asymptotics and Special Functions by Frank W. J. Olver.
Nonlinear dynamics and chaos by Steven H. Strogatz.

Difference Equations

Difference Equations: An Introduction with Applications by Walter G. Kelley and Allan C. Peterson.

Linear Algebra

Introduction to Linear Algebra by Gilbert Strang.
Fundamentals of MATRIX COMPUTATIONS by David S. Watkins.
A Multigrid Tutorial by D. Briggs
Matrix Computations by G. Golub and C. van Loan.
APPLIED LINEAR ALGEBRA: The Decoupling Principle by Lorenzo Sadun.
An Introduction to Multigrid Methods by Pieter Wesseling
Applications of Linear Algebra by Chris Rorres and Howard Anton
Matrices and Linear Transformations by Anthony J. Pettofrezzo.

General Numerics

Elementary Numerical Analysis An Algorithmic Approach by Samuel Daniel Conte and Carl de Boor (in progress)
A First Look at Numerical Functional Analysis by W. W. Sawyer
Numerical Methods that Work by Forman S. Acton
Numerical Computing With Matlab by Cleve Molder.
Finite-difference Equations and Simulations by Francis Begnaud Hildebrand.
Afternotes on Numerical Analysis by G. W. Stewart.
Numerical Methods Using Matlab by G. Lindfield and J. Penny
Numerical Methods in Engineering with Python by Jaan Kiusalaas


Introduction to Finite Mathematics by J. Kemeny, J. Snell, and G. Thompson.
An Introduction to Genetic Algorithms by Melanie Mitchell.
Practical Genetic Algorithms by Randy L. Haupt and Sue Ellen Haupt.
Numerical Optimization by J. Nocedal and S. Wright.
Optimum Seeking Methods by J. Wilde
Introduction to Linear Optimization by Dimitris Bertsimas and John N. Tsitsiklis.

Analytic Solution Techniques for Parital Differential Equations

An Introduction to the Method of Characteristics by Michael B. Abbott
Partial Differential Equations by Lawrence C. Evans.
Partial Differential Equations; Analytical Solution Techniques by J. Kevorkian.
Linear Integral Equations by Rainer Kress.
A Primer On Integral Equations of the First Kind by G. Milton Wing.
Nonlinear Partial Differential Equations for Scientists and Engineers by Lokenath Debnath.

Numerical Solution Techniques for Differential Equations

Solving ODEs with MATLAB by L.F. Shampine, I. Gladwell, S. Thompson

Numerical Computation of Internal and External Flows: Volume 1 & 2 by C. Hirsch
The Finite Element Method: Basic Concepts and Applications by D. Pepper and J. Heinrich.

Hyperbolic Systems

Finite Volume Methods for Hyperbolic Problems by Randall J. LeVeque.
Numerical Methods for Conservation Laws by Randall J. LeVeque.
Linear and Nonlinear Waves by Gerald Beresford Whitham.
Supersonic Flow and Shock Waves by Richard Courant.


Thermo-dynamics by Enrico Fermi.
Introduction to Thermal Physics by Daniel V. Schroeder
Statistical Physics by Gregory H. Wannier.
Fundamentals of Statistical and Thermal Physics by Frederick Reif.

Fluids/Solid Mechanics:

Stress Waves in Solids by H. Kolsky.
Mathematical Models of Fluiddynamics: An Introduction by Rainer Ansorge.
Elementary Fluid Dynamics by D. J. Acheson.
Introduction to Wave Propagation in Nonlinear Fluids and Solids by Douglas S. Drumheller.


A First Course in Probability by Sheldon Ross.
Introduction to PROBABILITY MODELS: Seventh Edition by Sheldon M. Ross.
Applied Probability Models with Optimization Applications by Sheldon M. Ross.
An Elementary Introduction to Mathematical Finance by Sheldon M. Ross.
Introduction to Stochastic Models by Roe Goodman.
Basic Concepts of Probability and Statistics by J. L. Hodges and E. L. Lehmann.

Mathematical Finance:

The Mathematics of Financial Derivatives by P. Wilmott
Paul Wilmott on Quantitative Finance by P. Wilmott
Frequently Asked Questions in Quantitative Finance by P. Wilmott
Computational Finance Using C and C# by Georege Levy.
Statistics and Data Analysis for Financial Engineering by David Ruppert
Empirical Market Microstructure by Joel Hasbrouck.

Classification/Decision Theory/Machine Learning/Statistics:

Mathematical Statistics and Data Analysis by John A. Rice.
An Introduction to Mathematical Statistics and Its Applications by Richard J. Larsen and Morris L. Marx.
Methods and Applications of Linear Models: Regression and the Analysis of Variance by Ronald Hocking.
Applied Linear Models with SAS by Daniel Zelterman.
Time Series Analysis: Forecasting and Control by George E. P. Box and Gwilym M. Jenkins.
Statistical Methods for Forecasting by Boyas Abraham and Johannes Ledolter.
Computational Statistics Handbook with Matlab by Wendy Martinez and Angel Martinez.
Exploratory Data Analysis with MATLAB by Wendy Martinez and Angel Martinez.
Reinforcement Learning: An Introduction by Richard Sutton and Andrew Barto
Approximate Dynamic Programming by Warren B. Powell
Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig
Pattern Recognition by Sergios Theodoridis and Konstantinos Koutroumbas
Pattern Classification and Scene Analysis (First Edition) by Richard Duda and Peter Hart
Pattern Classification (Second Edition) by Richard Duda, Peter Hart, and David Stork
The Elements of Statistical Learning by Jerome Friedman, Trevor Hastie, and Robert Tibshirani
An Introduction to Statistical Learning by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani
Applied Predictive Modeling by Max Kuhn and Kjell Johnson
Statistical Learning from a Regression Perspective by Richard A. Berk
Data Analysis and Graphics Using R: An Example-Based Approach by John Maindonald and W. John Braun
Detection, Estimation, and Modulation Theory Part 1 Harry L. Van Trees.
Detection, Estimation and Classification: An Introduction to Pattern Recognition and Related Topics by C. W. Therrien
Computer Approaches to Pattern Recognition by William S. Meisel.
Optimal Decision Theory by William DeGroot.
Optimal Control and Estimation by Robert F. Stengel.
Kalman Filtering Theory and Practice using MATLAB by Mohinder Grewal and Angus Andrews.
Applied Optimal Estimation edited by Arthur Gelb.
Classification, Parameter Estimation, and State Estimation by F. van der Heijden, R. P. W. Duin, D. de Ridder, and D. M. J. Tax.
Applied Linear Regression by Sanford Weisberg.
Residuals and Influence in Regression by R. Dennis Cook and Sanford Weisberg.
Probability and Statistics: For Engineering and the Sciences by Jay L. Devore
Resampling Methods: A Practical Guide to Data Analysis by Phillip Good
Pattern Recognition: A Statistical Approach by Pierre A. Devijver and Josef Kittler.
Basic Statistics: Understanding Conventional Methods and Modern Insights by Rand R. Wilcox.
Programming Collective Intelligence by Toby Segaran.
Introducing Monte Carlo Methods with R Christian P. Robert and George Casella.
Adaptive Filtering Primer by A. Poularikas and Z. Ramadan
Adaptive Filtering Theory by Symon Haykin
Principles of Adaptive Filters and Self-learning Systems by Anthony Zaknich.

Computer Science/Programming Languages:

SQL Practice Problems by Sylvia Moestl Vasilik.
Introduction to ALGORITHMS by T. Cormen, C. Leiserson, and R. Rivest.
Parallel Programming with MPI by Peter Pacheco
Introduction to Parallel Computing by Vipin Kumar, Ananth Grama, Anshul Gupta, & George Karypis.
Foundations of Multithreaded, Parallel, and Distributed Programming by Gregory R. Andrews
Unix Utilities by Ramkrishna S. Tare.
Learning Python by Mark Lutz & David Ascher.
Learning Perl by Randal L. Schwartz, Tom Phoenix, and Brian Foy.
THE ELEMENTS OF PROGRAMMING STYLE by Brian W. Kernighan and P. J. Plauger.

Misc Books:

Street-Fighting Mathematics by Sanjoy Mahajan
Codes, Ciphers, and Secret Writing by Martin Gardner
The Contest Problem Books: Annual High School Mathematics Contests
Fantastic Book of Math Puzzles by Margaret Edmiston
Puzzles to Puzzle You by Devi Shakuntala
How Would You Move Mt. Fuji? and Are You Smart Enough to Work at Google by William Poundstone
Signals and Systems by Alan Oppenheim and Alan Willsky
Elements of Information Theory by Thomas M. Cover and Joy A. Thomas
Computer Simulation Using Particles by R.W. Hockney and J.W. Eastwood
Topics in Applied Physics: Volume 25 Laser Beam Propagation in the Atmosphere; Edited by: John W. Strohbehn.
Understanding LASER technology: Second Edition by C. Breck Hitz.
Mechanics of Motor Proteins and the Cytoskeleton by Jonathon Howard.
Science & Music by Sir James Jeans.
Innumeracy: Mathematical Illiteracy and Its Consequences by John Allen Paulos.
Radar Principles for the Non-Specialist by J. C. Toomay.
Approximation Theory: From Taylor Polynomials to Wavelets by Ole Christensen and Khadija Laghrida Christensen.
Modeling Differential Equations in Biology by Clifford Henry Taubes.
Introduction to Graph Theory by Richard J. Trudeau.
Generatingfunctionology: Second Edition by Herbert S. Wilf.
Slicing Pizzas, Racing Turtles, and Further Adventures in Applied Mathematics by Robert B. Banks.