w2img::MovingAverageEstimator Class Reference

List of all members.

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Detailed Description

The moving average estimator works just like the Kalman Estimator, except that, instead of using a Kalman filter to estimate the true current value, it uses a moving average.

Author:

Lakshman

Version:

Id

w2img_KalmanEstimator.h,v 1.9 2009/06/02 20:17:57 lakshman Exp

Public Member Functions
void	update (float z_k, int MAXIMUM_HISTORY=5)
	update the filter with an observation.
float	getValue () const
	get the model value, which is the moving average.
void	getMeanStdDev (float *mean, float *std_deviation) const
	get the model's std-deviation

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Member Function Documentation

void w2img::MovingAverageEstimator::getMeanStdDev	(	float *	mean,
		float *	std_deviation
	)			const

get the model's std-deviation

float w2img::MovingAverageEstimator::getValue

(

)

const

get the model value, which is the moving average.

void w2img::MovingAverageEstimator::update	(	float	z_k,
		int	MAXIMUM_HISTORY = 5
	)

update the filter with an observation.

Specify also how many previous observations should be used. This will automatically prune the list of observations held to that number. The default is to use 5 numbers.

If MAXIMUM_HISTORY is negative, an unlimited history will be used. WARNING: unlike the Kalman estimator, this is very expensive memory-wise since we have to store all the data. Also, unlike the Kalman estimator, there is no way for the moving average to place more weight on later observations, so a positive MAXIMUM_HISTORY is recommended.

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