ITK
4.2.0
Insight Segmentation and Registration Toolkit
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#include <itkParticleSwarmOptimizer.h>
Static Public Member Functions | |
static Pointer | New () |
Protected Member Functions | |
ParticleSwarmOptimizer () | |
void | PrintSelf (std::ostream &os, Indent indent) const |
virtual void | UpdateSwarm () |
virtual | ~ParticleSwarmOptimizer () |
Protected Member Functions inherited from itk::ParticleSwarmOptimizerBase | |
void | FileInitialization () |
virtual void | Initialize () |
ParticleSwarmOptimizerBase () | |
ParticleSwarmOptimizerBase (const Self &) | |
void | PrintParamtersType (const ParametersType &x, std::ostream &os) const |
void | RandomInitialization () |
virtual void | ValidateSettings () |
virtual | ~ParticleSwarmOptimizerBase () |
Protected Member Functions inherited from itk::SingleValuedNonLinearOptimizer | |
SingleValuedNonLinearOptimizer () | |
virtual | ~SingleValuedNonLinearOptimizer () |
NonLinearOptimizer () | |
virtual | ~NonLinearOptimizer () |
Protected Member Functions inherited from itk::Optimizer | |
Optimizer () | |
virtual void | SetCurrentPosition (const ParametersType ¶m) |
virtual | ~Optimizer () |
Protected Member Functions inherited from itk::Object | |
Object () | |
bool | PrintObservers (std::ostream &os, Indent indent) const |
virtual void | SetTimeStamp (const TimeStamp &time) |
virtual | ~Object () |
Protected Member Functions inherited from itk::LightObject | |
virtual LightObject::Pointer | InternalClone () const |
LightObject () | |
virtual void | PrintHeader (std::ostream &os, Indent indent) const |
virtual void | PrintTrailer (std::ostream &os, Indent indent) const |
virtual | ~LightObject () |
Private Member Functions | |
void | operator= (const Self &) |
ParticleSwarmOptimizer (const Self &) |
Private Attributes | |
ParametersType::ValueType | m_GlobalCoefficient |
ParametersType::ValueType | m_InertiaCoefficient |
ParametersType::ValueType | m_PersonalCoefficient |
Additional Inherited Members | |
Protected Attributes inherited from itk::ParticleSwarmOptimizerBase | |
CostFunctionType::MeasureType | m_FunctionBestValue |
std::vector< MeasureType > | m_FunctionBestValueMemory |
CostFunctionType::MeasureType | m_FunctionConvergenceTolerance |
bool | m_InitializeNormalDistribution |
NumberOfIterationsType | m_IterationIndex |
NumberOfIterationsType | m_MaximalNumberOfIterations |
NumberOfGenerationsType | m_NumberOfGenerationsWithMinimalImprovement |
NumberOfParticlesType | m_NumberOfParticles |
ParameterBoundsType | m_ParameterBounds |
ParametersType | m_ParametersBestValue |
ParametersType | m_ParametersConvergenceTolerance |
std::vector< ParticleData > | m_Particles |
double | m_PercentageParticlesConverged |
bool | m_PrintSwarm |
RandomVariateGeneratorType::IntegerType | m_Seed |
std::ostringstream | m_StopConditionDescription |
bool | m_UseSeed |
Protected Attributes inherited from itk::SingleValuedNonLinearOptimizer | |
CostFunctionPointer | m_CostFunction |
Implementation of a Particle Swarm Optimization (PSO) algorithm.
The PSO algorithm was originally presented in:
J. Kennedy, R. Eberhart, "Particle Swarm Optimization", Proc. IEEE Int. Neural Networks, 1995.
The algorithm uses a stochastic optimization approach. Optimization is performed by maintaining a swarm (flock) of particles that traverse the parameter space, searching for the optimal function value. Associated with each particle are its location and speed, in parameter space. A particle's next location is determined by its current location, its current speed, the location of the best function value it previously encountered, and the location of the best function value the particles in its neighborhood previously encountered. In this implementation we use a global neighborhood with the following update equations:
where are and are user selected weights.
Swarm initialization is performed within the user supplied parameter bounds using a uniform distribution or a normal distribution centered on the initial parameter values supplied by the user. The search terminates when the maximal number of iterations has been reached or when the change in the best value in the past generations is below a threshold and the swarm has collapsed (i.e. particles are close to each other in parameter space).
NOTE: This implementation only performs minimization.
Definition at line 59 of file itkParticleSwarmOptimizer.h.
typedef SmartPointer<const Self> itk::ParticleSwarmOptimizer::ConstPointer |
Reimplemented from itk::ParticleSwarmOptimizerBase.
Definition at line 67 of file itkParticleSwarmOptimizer.h.
Reimplemented from itk::ParticleSwarmOptimizerBase.
Definition at line 66 of file itkParticleSwarmOptimizer.h.
Standard "Self" typedef.
Reimplemented from itk::ParticleSwarmOptimizerBase.
Definition at line 64 of file itkParticleSwarmOptimizer.h.
Reimplemented from itk::ParticleSwarmOptimizerBase.
Definition at line 65 of file itkParticleSwarmOptimizer.h.
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Create an object from an instance, potentially deferring to a factory. This method allows you to create an instance of an object that is exactly the same type as the referring object. This is useful in cases where an object has been cast back to a base class.
Reimplemented from itk::SingleValuedNonLinearOptimizer.
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Run-time type information (and related methods).
Reimplemented from itk::ParticleSwarmOptimizerBase.
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Method for creation through the object factory.
Reimplemented from itk::SingleValuedNonLinearOptimizer.
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Types inherited from the superclass
Reimplemented from itk::ParticleSwarmOptimizerBase.
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Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes.
Reimplemented from itk::ParticleSwarmOptimizerBase.
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The Particle swarm optimizer uses the following update formula: v_i(t+1) = w*v_i(t) + c_1*uniform(0,1)*(p_i-x_i(t)) + c_2*uniform(0,1)*(p_g-x_i(t)) x_i(t+1) = clampToBounds(x_i(t) + v_i(t+1)) where w - inertia constant c_1 - personal coefficient c_2 - global coefficient p_i - parameters yielding the best function value obtained by this particle p_g - parameters yielding the best function value obtained by all particles
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Implement your update rule in this function.
Implements itk::ParticleSwarmOptimizerBase.
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Definition at line 106 of file itkParticleSwarmOptimizer.h.
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Definition at line 104 of file itkParticleSwarmOptimizer.h.
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Definition at line 105 of file itkParticleSwarmOptimizer.h.