books (available in the library, some in pdf):
2. D. G. Luenberger,
Linear and Nonlinear Programming, Springer, 2005.
3. J. Brinkhuis,
V. Tikhomirov, Optimization: Insights and
Applications, Princeton, 2005.
4. R. Fletcher, Practical Methods of
Optimization, Wiley, 2000.
5. K. Lange, Optimization, Springer,
6. C.L. Byrne, A First Course in
Optimization, available at http://faculty.uml.edu/cbyrne/opttext.pdf
7. M. Aoki, Introduction to
Optimization Techniques. Macmillan, 1971.
Some more references (deep but
8. D.P. Bertsekas,
Nonlinear Programming, Athena Scientific, 2nd Ed., 2008.
9. A. Ben-Tal, A. Nemirovski,
Lectures on Modern Convex Optimization: Analysis, Algorithms, and Engineering
10. D. G. Luenberger,
Optimization by Vector Space Methods, Wiley-Interscience;
11. D.P. Bertsekas,
A. Nedic, A,E. Ozdaglar, Convex Analysis and Optimization,
Athena Scientific, 2003.
12. A.G. Suharev,
A.B. Timoxov, B.B. Fedorov,
A Course of Optimization Methods, FML, Moscow,
2005 (in Russian).
13. B.M. Alekseev, E.M. Galeev, B.M. Tihomirov,
Problems in Optimization Theory, FML, Moscow,
2005 (in Russian).
14. B.T. Polayk,
Introduction to Optimization, Nauka, Moscow, 1983 (in
15. A.J. Laub, Matrix Analysis for Scientists and
2005. - this
is a good introductory book with discussion of basic techniques and results
in linear algebra and matrix theory.
16. F. Zhang, Matrix Theory, Springer, 1999. this is a more
comprehensive textbook of matrix theory, with many end-of-chapter problems.
R.A. Horn, C.R. Johnson, Matrix Analysis, Cambridge University
and the 2nd volume (next) is a comprehensive book, which treats in detail all
important methods and results in matrix theory; it is very well written and
end-of-chapter problems are well-selected. Strongly recommended, especially
if you use matrix theory in your research.
18. R.A. Horn, C.R. Johnson, Topics in
Matrix Analysis, Cambridge
University Press, 1991.
see the comments for # 14.
19. D.S. Bertstein, Matrix Mathematics, Princeton University Press, 2005. - this is an
extensive handbook with many facts and formulas involving matrices, which are
well categorized and handy to use (but this is not a textbook - you cannot
learn matrix theory from it).
Cookbook - a handbook on matrices, pdf is available.
20a. R. Bronson, Matrix Operations, McGraw Hill, 2011. a
handbook on matrices/linear algebra with many solved problems.
Optimization in Communications/Signal Processing/Networks
21. D. P. Palomar and Y. Jiang, MIMO transceiver design via majorization
theory, Found. Trends Commun. Inf. Theory, vol. 3,
no. 4-5, pp. 331551, 2006
22. M. Chiang, Geometric Programming for Communication Systems, Foundations
and Trends in Communications and Information Theory, Vol. 2, No 1/2 (2005)
23. E. Jorswieck, H. Boche,
Majorization and Matrix-Monotone Functions in Wireless Communications,
Foundations and Trends in Communications and Information Theory, Vol. 3, No.
6 (2006) 553701.
24. M. Chiang, P. Hande, T. Lan, Power Control in
Wireless Cellular Networks, Foundations and Trends in Networking, Vol. 2, No.
4 (2007) 381533.
25. M. Chiang et al, Layering as Optimization Decomposition: A Mathematical
Theory of Network Architectures, Proceedings of the IEEE, Vol. 95, No. 1,
26. P.P. Vaidyanathan, S.M. Phoong,
Y.P. Lin, Signal Processing and Optimization for Transceiver Systems, Cambridge University Press, 2010.
27. E. Bjφrnson and E. Jorswieck,
"Optimal Resource Allocation in Coordinated Multi-Cell Systems,"
Foundations and Trends in Communications and Information Theory, vol. 9, no.
23, pp. 113-381, Jan. 2013.
28. Y. J. Zhang, L. Qian, and J. Huang, "Monotonic Optimization in
Communication and Networking Systems," Foundations and Trends in
Networking, vol. 7, no. 1, pp. 1-75, Oct. 2013.