| Prev | Next | _reference |
| C | |
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constraint | Computes the Control Constraint Function |
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control | The Control Test Problem |
| F | |
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full_newton | Execute Full Newton Steps For Control Constraint |
| I | |
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implicit_ad | AD Methods That Differentiate Implicit Functions |
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implicit_kedem | Kedem Method for Derivatives of Implicit Functions |
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implicit_newton | Newton Step Method for Derivatives of Implicit Functions |
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implicit_solver | Control Problem Solver for Implicit Kedem or Newton Object |
| J | |
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jac_constraint | Compute Jacobian of Implicit Function Constraints |
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join_vector | Join Two Vectors |
| L | |
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license | Implicit AD License |
| N | |
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norm_squared | Norm Squared of a Vector |
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notation | Notation |
| O | |
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objective | Computes the Control Objective Function |
| R | |
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rec_constraint | Record the Control Constraint as a CppAD Function Object |
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rec_objective | Record the Control Objective |
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repeat_kedem_gradient | Repeated Computation of Control Problem Gradient Using Kedem Method |
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repeat_kedem_hessian | Repeated Computation of Control Problem Hessian Using Kedem Method |
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repeat_newton_gradient | Repeated Computation of Control Problem Gradient Using Newton Method |
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repeat_newton_hessian | Repeated Computation of Control Problem Hessian Using Newton Method |
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run_cmake.sh | Run CMake to Configure Implicit AD |
| S | |
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set_T_p_and_q | Set T, p, and q |
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solve_lower_cppad | Solve a CppAD Sparse Lower Triangular System |
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sparse_cppad2eigen | Convert A CppAD Sparse Matrix to an Eigen Sparse Matrix |
| T | |
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test_circle_implicit_kedem | Example / Test of Implicit Wagner Class |
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test_circle_implicit_newton | Example / Test of Implicit Newton Class |
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test_control_reduced_objective | Example / Test of Control Problem Reduced Objective |
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time | Timing Comparison of Methods |
| U | |
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utility | Utilities Used by All Methods |
| V | |
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vector_matrix | Conversions Between Control Vectors and Matrices |