Optimization Toolbox    

Index


active constraints <1> <2> <3>
active set method <1> <2> <3> <4> <5>
arguments, additional
attainment factor
axis crossing. See zero of a function

banana function
BFGS formula <1> <2> <3>
bisection search
bound constraints, large-scale
box constraints. See bound constraints

centering parameter
CG. See conjugate gradients
code
updating to Version 2 syntax
complementarity conditions
complex values
complex variables <1> <2>
conjugate gradients
constrained minimization
large-scale example <1> <2>
medium-scale example
constraints
linear <1> <2> <3>
positive
continuous function and gradient methods
conventions in our documentation (table)
convex problem
cubic interpolation
curve-fitting
categories
functions that apply

data-fitting
categories
functions that apply
dense columns, constraint matrix
DFP formula
direction of negative curvature
discontinuities <1> <2>
discontinuous problems <1> <2>
discrete variables
dual problem
duality gap

-constraint method
equality constraints
dense columns
medium-scale example
equality constraints inconsistent warning, quadprog
equality constraints, linear
large-scale
equation solving
categories
functions that apply
error, Out of memory.

feasibility conditions
feasible point, finding
fgoalattain
example
fixed variables
fixed-step ODE solver
fminbnd
fmincon
large-scale example <1> <2>
medium-scale example
fminimax
example
fminsearch
fminunc
large-scale example
medium-scale example
warning messages
fseminf
fsolve
large-scale example
medium-scale example
function arguments
function discontinuities
functions
grouped by type of optimization
updating to Version 2
fzero

Gauss-Newton
Gauss-Newton method <1> <2> <3> <4> <5> <6>
global minimum
global variables
goal attainment <1> <2>
example
goaldemo
golden section search
gradient checking, analytic
gradient examples
gradient function
gradient methods

Hessian modified message
Hessian modified twice message
Hessian sparsity structure
Hessian update <1> <2>

inconsistent constraints
indefinite problems
infeasible message
infeasible problems
infeasible solution warning
linprog
quadprog
infinite loop
inline objects
input arguments
integer variables
interior-point linear programming
introduction to optimization
iterative display

Jacobian examples
Jacobian sparsity pattern

Kuhn-Tucker equations

Lagrange multipliers
large-scale linear programming
large-scale functionality coverage
large-scale methods
demos
examples
least squares
categories
functions that apply
Levenberg-Marquardt method <1> <2> <3> <4> <5>
line search <1> <2> <3> <4> <5>
line search strategy
linear constraints <1> <2> <3>
linear equations solve
linear least squares
constrained
large-scale algorithm
large-scale example
nonnegative
unconstrained
linear programming
implementation
large-scale algorithm
large-scale example <1> <2>
problem
linprog
large-scale example <1> <2>
LIPSOL
lower bounds
lsqcurvefit
lsqlin
large-scale example
lsqnonlin
convergence
large-scale example
medium-scale example
lsqnonneg

maximization
medium-scale methods
demos
Mehrotra's predictor-corrector algorithm <1> <2>
merit function
minimax examples
minimax problem, solving
minimization
categories
functions that apply
multiobjective optimization <1> <2>
examples

NCD. See Nonlinear Control Design
negative curvature direction <1> <2>
negative definite problems
Nelder and Mead
Newton direction
approximate
Newton's method
no update message
nonconvex problems
noninferior solution
Nonlinear Control Design (NCD) Blockset
nonlinear data-fitting
nonlinear equations, solving
nonlinear least squares <1> <2> <3>
large-scale algorithm
large-scale example
nonlinear programming
nonlinear system of equations, large-scale example
normal equations <1> <2>

objective function
objective function, undefined values
optimality conditions linear programming
optimget
optimization
functions for each type
introduction
optimization parameters structure <1> <2> <3>
optimset
options parameters
descriptions
possible values
utility functions
Out of memory. error
output arguments
output display
output headings
large-scale algorithms
medium-scale algorithms

PCG. See preconditioned conjugate gradients
preconditioned conjugate gradients <1> <2> <3>
algorithm
preconditioner <1> <2>
banded
predictor-corrector algorithm
preprocessing
linear programming <1> <2>
primal problem
primal-dual algorithm
primal-dual interior-point
projection method <1> <2>

quadprog
large-scale example
quadratic interpolation
quadratic programming <1> <2> <3>
large-scale algorithm
large-scale example
quasi-Newton method <1> <2> <3>

reflective line search
reflective steps <1> <2>
residual
Rosenbrock's function

sampling interval
secular equation
semi-infinite constraints
Sherman-Morrison formula
signal processing example
simple bounds
simplex search <1> <2>
Simulink, multiobjective example
singleton rows
sparsity pattern Jacobian
sparsity structure, Hessian
SQP method <1> <2> <3>
steepest descent
stopping criteria, large-scale linear programming
structural rank
subspace
determination of
subspace, two-dimensional
syntax
updating to Version 2
system of equations, solving

trust region
two-dimensional subspace
typographical conventions

unbounded solutions warning
linprog
quadprog
unconstrained minimization <1> <2>
large-scale example
medium-scale example
one dimensional
unconstrained optimization
updating code to Version 2 syntax
upper bounds

variable-step ODE solver
Version 2
changes to calling sequence
converting Version 1.5 code

warning
equality constraints inconsistent, quadprog
infeasible solution, linprog
infeasible solution, quadprog
stuck at minimum, fsolve
unbounded solutions, linprog
unbounded solutions, quadprog
warnings displayed
weighted sum strategy

zero curvature direction
zero finding
zero of a function, finding

quadprog