ptolemy.domains.continuous.lib
Class Noise
java.lang.Object
ptolemy.kernel.util.NamedObj
ptolemy.kernel.InstantiableNamedObj
ptolemy.kernel.Entity
ptolemy.kernel.ComponentEntity
ptolemy.actor.AtomicActor
ptolemy.actor.TypedAtomicActor
ptolemy.actor.lib.Source
ptolemy.actor.lib.RandomSource
ptolemy.actor.lib.Gaussian
ptolemy.domains.continuous.kernel.Noise
ptolemy.domains.continuous.lib.Noise
- All Implemented Interfaces:
- java.io.Serializable, java.lang.Cloneable, Actor, Executable, FiringsRecordable, Initializable, TypedActor, Changeable, Debuggable, DebugListener, Derivable, Instantiable, ModelErrorHandler, MoMLExportable, Moveable, Nameable
public class Noise
- extends Noise
This actor generates continuous-time noise with a Gaussian distribution.
It provides two rather ad-hoc approximations to a white noise process, depending
on the value of the linearlyInterpolate parameter. Specifically,
if this parameter is true (the default), then the output signal is
a continuous signal that linearly interpolates between
Gaussian random numbers generated at each sample time chosen by
the solver. If the solver step size is constant or increasing, then these Gaussian
random numbers will be independent. However, if the solver finds itself having
to reduce the step size after performing a speculative execution into the
future, then the random number produced at the end of the reduced
integration step will be correlated with that produced at the beginning
of the integration step. (FIXME: Need a figure to illustrate this.)
If linearlyInterpolate is set to false, then this actor will
hold the value of its output constant for the duration of an integration
step. Thus, the output signal is piecewise constant. At each time step
chosen by the solver, the value is given by a new independent Gaussian
random number. This method has the advantage that samples at all
times chosen by the solver are uncorrelated.
In both cases, whether linearlyInterpolate is true or false, if the
solver holds its step size constant, then the resulting signal is
statistically equivalent to filtered white noise. If linearlyInterpolate
is true, then the power spectrum has the shape of a sinc squared.
If it is false, then it has the shape of the absolute value of a sinc
function. In the latter case, the power is infinite, so the approximation
is not physically realizable. In the former case, the power is finite.
In both cases, sampling the process at the rate of one over the step
size yields a discrete-time white noise process.
It is worth explaining why we must approximate white noise.
In general, it is not possible in any discretized approximation of a continuous
random process to exactly simulate a white noise process. By definition, a
white noise process is one where any two values at distinct times are
uncorrelated. A naive attempt to simulate this might simply generate
a new random number at each sample time at which the solver chooses
to fire the actor. However, this cannot work in general.
Specifically, the semantics of the continuous domain assumes
that signals are piecewise continuous. The signal resulting from
the above strategy will not be piecewise continuous. If the solver
refines a step size and chooses a point close to a previously calculated
point, the new value produced by such an actor would not be close to the
previously value previously produced. This can result in the solver
assuming that its step size is too large and reducing it until it can
reduce it no more.
To demonstrate this effect, try connecting a GaussianActor to a
LevelCrossingDetector actor under a ContinuousDirector. An execution
of the model will immediately trigger an exception with a message
like "The refined step size is less than the time resolution, at time..."
Conceptually, with a true white noise process, the level crossing
occurs at all times, and therefore the exception is,
in fact, the correct response.
If you modify the above example by sending the output of the
Gaussian actor directly to an Integrator, and then the output
of the Integrator to the LevelCrossingDetector, then the exception
disappears. The Integrator ensures that the signal is piecewise
continuous. This might seem like a reasonable approximation to a
Weiner process, but in fact it is problematic. In particular,
at the times that the LevelCrossingDetector triggers, the
Gaussian actor will actually produce two distinct random numbers
at the same time (at different microsteps). This changes the
statistics of the output in a very subtle way.
Note that a much more principled noise process is generated
by the BandlimitedNoise actor.
- Since:
- Ptolemy II 8.0
- Version:
- $Id: Noise.java 57044 2010-01-27 22:41:05Z cxh $
- Author:
- Edward A. Lee
- See Also:
- Serialized Form
- Accepted Rating:
- Proposed Rating:
| Fields inherited from class ptolemy.kernel.util.NamedObj |
_changeListeners, _changeLock, _changeRequests, _debugging, _debugListeners, _elementName, _isPersistent, _verbose, _workspace, ATTRIBUTES, CLASSNAME, COMPLETE, CONTENTS, DEEP, FULLNAME, LINKS |
|
Constructor Summary |
Noise(CompositeEntity container,
java.lang.String name)
Construct an actor with the given container and name. |
| Methods inherited from class ptolemy.actor.AtomicActor |
_actorFiring, _actorFiring, addActorFiringListener, addInitializable, connectionsChanged, createReceivers, declareDelayDependency, getCausalityInterface, getDirector, getExecutiveDirector, getManager, inputPortList, isFireFunctional, isStrict, iterate, newReceiver, outputPortList, preinitialize, pruneDependencies, recordFiring, removeActorFiringListener, removeDependency, removeInitializable, setContainer, stop, stopFire, terminate, wrapup |
| Methods inherited from class ptolemy.kernel.ComponentEntity |
_adjustDeferrals, _checkContainer, _getContainedObject, _propagateExistence, getContainer, instantiate, isAtomic, isOpaque, moveDown, moveToFirst, moveToIndex, moveToLast, moveUp, propagateExistence, setName |
| Methods inherited from class ptolemy.kernel.Entity |
_description, _exportMoMLContents, _removePort, _validateSettables, connectedPortList, connectedPorts, containedObjectsIterator, getAttribute, getPort, getPorts, linkedRelationList, linkedRelations, portList, removeAllPorts, setClassDefinition, uniqueName |
| Methods inherited from class ptolemy.kernel.util.NamedObj |
_addAttribute, _adjustOverride, _attachText, _cloneFixAttributeFields, _debug, _debug, _debug, _debug, _debug, _getIndentPrefix, _isMoMLSuppressed, _markContentsDerived, _propagateValue, _recordDecoratedAttributes, _removeAttribute, _splitName, _stripNumericSuffix, addChangeListener, addDebugListener, attributeList, attributeList, deepContains, depthInHierarchy, description, description, event, executeChangeRequests, exportMoML, exportMoML, exportMoML, exportMoML, exportMoMLPlain, getAttribute, getAttributes, getChangeListeners, getClassName, getDecoratorAttribute, getDecoratorAttributes, getDerivedLevel, getDerivedList, getDisplayName, getFullName, getModelErrorHandler, getName, getName, getSource, handleModelError, isDeferringChangeRequests, isOverridden, isPersistent, lazyContainedObjectsIterator, message, propagateValue, propagateValues, removeChangeListener, removeDebugListener, requestChange, setClassName, setDeferringChangeRequests, setDerivedLevel, setDisplayName, setModelErrorHandler, setPersistent, setSource, sortContainedObjects, toplevel, toString, validateSettables, workspace |
| Methods inherited from class java.lang.Object |
equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Noise
public Noise(CompositeEntity container,
java.lang.String name)
throws NameDuplicationException,
IllegalActionException
- Construct an actor with the given container and name.
- Parameters:
container - The container.name - The name of this actor.
- Throws:
IllegalActionException - If the actor cannot be contained
by the proposed container.
NameDuplicationException - If the container already has an
actor with this name.