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CHAPTER 1 NECESSARY CONDITIONS FOR AN EXTREMUM
CHAPTER 2 NECESSARY CONDITIONS FOR AN EXTREMUM IN THE CLASSICAL PROBLEMS OF THE CALCULUS OF VARIATIONS AND...
CHAPTER 3 ELEMENTS OF CONVEX ANALYSIS
CHAPTER 4 LOCAL CONVEX ANALYSIS
CHAPTER 5 LOCALLY CONVEX PROBLEMS AND THE MAXIMUM PRINCIPLE FOR PROBLEMS WITH PHASE CONSTRAINTS
CHAPTER 6 SPECIAL PROBLEMS
CHAPTER 7 SUFFICIENT CONDITIONS FOR AN EXTREMUM
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absolutely continuous assertion assume assumption Banach space boundary conditions bounded calculus of variations called Chapter classical calculus closed compact consider continuous linear continuously differentiable conv converges convex function convex set Corollary defined definition denote derivative domain epif equality Euler equation exists a number extremal problems extremum f is continuous finite fo(x formula Frechet differentiable function f implies int(dom integral interval K-function Lagrange function Lagrange multipliers Lemma Let f linear functional locally convex lower semicontinuous mapping F maximum principle minimum multimapping necessary conditions neighborhood non-empty non-negative obtain optimal control optimal control problems phase constraints point x0 Proof proper convex function Proposition proved quadratic form relation satisfies sequence ſº solution subdifferential subset subspace sufficient conditions summable theorem theory topological space topology vector vector-valued function weakly Weierstrass zero