Fundamentals of Constrained Optimization
The material presented so far dealt largely with principles, methods, and algorithms for unconstrained optimization. In this and the next five chapters, we build on the introductory principles of constrained optimization discussed in Secs. 1.4–1.6 and proceed to examine the underlying theory and structure of some very sophisticated and efficient constrained optimization algorithms.
KeywordsLagrange Multiplier Equality Constraint Inequality Constraint Linear Programming Problem Feasible Region
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- 9.A. Antoniou, Digital Signal Processing: Signals, Systems, and Filters, McGraw-Hill, New York, 2005.Google Scholar
- 10.W.-S. Lu, “A parameterization method for the design of IIR digital filters with prescribed stability margin,” in Proc. Int. Symp. Circuits Syst., pp. 2381–2384, June 1997.Google Scholar
- 12.H. W. Kuhn and A. W. Tucker, “Nonlinear programming,” in Proc. 2nd Berkeley Symp., pp. 481–492, Berkeley, CA, 1951.Google Scholar