A

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

B

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

C

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

D

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

E

-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.

F

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

G

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

H

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

I

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

J

Jacobian examples
Jacobian sparsity pattern

K

Kuhn-Tucker equations

L

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

M

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

N

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>

O

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

P

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>

Q

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

R

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

S

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

T

trust region
two-dimensional subspace
typographical conventions

U

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

V

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

W

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

Z

zero curvature direction
zero finding
zero of a function, finding