Introduction to Matrix Computations
āĻā§āĻ¨ ā§§ā§¯ā§ā§Š ¡ Elsevier
āĻāĻŦā§āĻ
441
āĻĒā§āĻˇā§āĻ āĻž
family_home
āĻ¯ā§āĻā§āĻ¯
info
reportāĻŽā§āĻ˛ā§āĻ¯āĻžāĻāĻāĻ¨ āĻā§°ā§ āĻĒā§°ā§āĻ¯āĻžāĻ˛ā§āĻāĻ¨āĻž āĻ¸āĻ¤ā§āĻ¯āĻžāĻĒāĻ¨ āĻā§°āĻž āĻšā§ā§ąāĻž āĻ¨āĻžāĻ  āĻ
āĻ§āĻŋāĻ āĻāĻžāĻ¨āĻ
āĻāĻ āĻāĻŦā§āĻāĻāĻ¨ā§° āĻŦāĻŋāĻˇā§ā§
Numerical linear algebra is far too broad a subject to treat in a single introductory volume. Stewart has chosen to treat algorithms for solving linear systems, linear least squares problems, and eigenvalue problems involving matrices whose elements can all be contained in the high-speed storage of a computer. By way of theory, the author has chosen to discuss the theory of norms and perturbation theory for linear systems and for the algebraic eigenvalue problem. These choices exclude, among other things, the solution of large sparse linear systems by direct and iterative methods, linear programming, and the useful Perron-Frobenious theory and its extensions. However, a person who has fully mastered the material in this book should be well prepared for independent study in other areas of numerical linear algebra.
āĻāĻ āĻāĻŦā§āĻāĻāĻ¨āĻ āĻŽā§āĻ˛ā§āĻ¯āĻžāĻāĻāĻ¨ āĻā§°āĻ
āĻāĻŽāĻžāĻ āĻāĻĒā§āĻ¨āĻžā§° āĻŽāĻ¤āĻžāĻŽāĻ¤ āĻāĻ¨āĻžāĻāĻāĨ¤
āĻĒāĻĸāĻŧāĻžā§° āĻ¨āĻŋāĻ°ā§āĻĻā§āĻļāĻžā§ąāĻ˛ā§
āĻ¸ā§āĻŽāĻžā§°ā§āĻāĻĢâāĻ¨ āĻā§°ā§ āĻā§āĻŦāĻ˛ā§āĻ
Android āĻā§°ā§ iPad/iPhoneā§° āĻŦāĻžāĻŦā§ Google Play Books āĻāĻĒāĻā§ āĻāĻ¨āĻˇā§āĻāĻ˛ āĻā§°āĻāĨ¤ āĻ āĻ¸ā§āĻŦāĻ¯āĻŧāĻāĻā§āĻ°āĻŋāĻ¯āĻŧāĻāĻžā§ąā§ āĻāĻĒā§āĻ¨āĻžā§° āĻāĻāĻžāĻāĻŖā§āĻā§° āĻ¸ā§āĻ¤ā§ āĻāĻŋāĻāĻ āĻšāĻ¯āĻŧ āĻā§°ā§ āĻāĻĒā§āĻ¨āĻŋ āĻ¯'āĻ¤ā§ āĻ¨āĻžāĻĨāĻžāĻāĻ āĻ¤'āĻ¤ā§āĻ āĻā§āĻ¨ā§ āĻ
āĻĄāĻŋāĻ
'āĻŦā§āĻ āĻ
āĻ¨āĻ˛āĻžāĻāĻ¨ āĻŦāĻž āĻ
āĻĢāĻ˛āĻžāĻāĻ¨āĻ¤ āĻļā§āĻ¨āĻŋāĻŦāĻ˛ā§ āĻ¸ā§āĻŦāĻŋāĻ§āĻž āĻĻāĻŋāĻ¯āĻŧā§āĨ¤
āĻ˛ā§āĻĒāĻāĻĒ āĻā§°ā§ āĻāĻŽā§āĻĒāĻŋāĻāĻāĻžā§°
āĻāĻĒā§āĻ¨āĻŋ āĻāĻŽā§āĻĒāĻŋāĻāĻāĻžā§°ā§° ā§ąā§āĻŦ āĻŦā§āĻ°āĻžāĻāĻāĻžā§° āĻŦā§āĻ¯ā§ąāĻšāĻžā§° āĻā§°āĻŋ Google PlayāĻ¤ āĻāĻŋāĻ¨āĻž āĻ
āĻĄāĻŋāĻ
'āĻŦā§āĻāĻ¸āĻŽā§āĻš āĻļā§āĻ¨āĻŋāĻŦ āĻĒāĻžā§°ā§āĨ¤
āĻ-ā§°ā§āĻĄāĻžā§° āĻā§°ā§ āĻ
āĻ¨ā§āĻ¯ āĻĄāĻŋāĻāĻžāĻāĻ
Kobo eReadersā§° āĻĻā§°ā§ āĻ-āĻāĻŋā§āĻžāĻāĻšā§ā§° āĻĄāĻŋāĻāĻžāĻāĻāĻ¸āĻŽā§āĻšāĻ¤ āĻĒā§āĻŋāĻŦāĻ˛ā§, āĻāĻĒā§āĻ¨āĻŋ āĻāĻāĻž āĻĢāĻžāĻāĻ˛ āĻĄāĻžāĻāĻ¨āĻ˛âāĻĄ āĻā§°āĻŋ āĻ¸ā§āĻāĻā§ āĻāĻĒā§āĻ¨āĻžā§° āĻĄāĻŋāĻāĻžāĻāĻāĻ˛ā§ āĻ¸ā§āĻĨāĻžāĻ¨āĻžāĻ¨ā§āĻ¤ā§°āĻŖ āĻā§°āĻŋāĻŦ āĻ˛āĻžāĻāĻŋāĻŦāĨ¤ āĻ¸āĻŽā§°ā§āĻĨāĻŋāĻ¤ āĻ-ā§°āĻŋāĻĄāĻžā§°āĻ˛ā§ āĻĢāĻžāĻāĻ˛āĻā§ āĻā§āĻ¨ā§āĻā§ āĻ¸ā§āĻĨāĻžāĻ¨āĻžāĻ¨ā§āĻ¤ā§° āĻā§°āĻŋāĻŦ āĻāĻžāĻ¨āĻŋāĻŦāĻ˛ā§ āĻ¸āĻšāĻžāĻ¯āĻŧ āĻā§āĻ¨ā§āĻĻā§ā§°āĻ¤ āĻĨāĻāĻž āĻ¸āĻŦāĻŋāĻļā§āĻˇ āĻ¨āĻŋā§°ā§āĻĻā§āĻļāĻžā§ąāĻ˛ā§ āĻāĻžāĻāĻāĨ¤
