BPE V1.0
29-SEP-1991
Ralph Zazula
zazula@bonehead.tucson.az.us

BackPropEngine

INHERITS FROM	Object

DECLARED IN	BackPropEngine.h

CLASS DESCRIPTION

This class implements a feed-forward network that updates it's weights using the Error Back-propagation algorithm.

INSTANCE VARIABLES

Inherited from Object	Class	isa;

Declared in BackPropEngine 	id	inputs;
	id	hidden;
	id	outputs;
	float	ETA;
	float	ALPHA;

inputs	a List of the input Neurons
hidden	a List of the hidden layer Neurons
outputs	a List of the output Neurons
ETA	the learning-rate
ALPHA	the momentum-term (not used)

METHOD TYPES

Initializing a new instance	± init
	± initWithInputs:hidden:outputs:

Running the algorithm	± applyInput:
 	± correctWithTarget:
	
Getting parameters	± inputs
 	± hidden
	± outputs

INSTANCE METHODS

applyInput:
- applyInput:(double *)input

Feeds the input vector pointed to by input forward through the BP network.

correctWithTarget:
- correctWithTarget:(double *)target

Modifies the weights of the BP network by comparing the current output to the target vector target.  This assumes that you have used the applyInput: method to feed-forward an input vector.

See also:  - applyInput:

hidden
- hidden

Returns a pointer to the receivers list of hidden Neurons.

init
- init

Initializes the receiver.  This should not be called directly.  Use initWithInputs:hidden:outputs: to initialize a new BackPropEngine.

See also: ± initWithInputs:hidden:outputs:

initWithInputs:hidden:outputs:
- initWithInputs:(int)Nin hidden:(int)Nhid outputs:(int)Nout

Initializes the receiver creating a feed-forward BP network with Nin inputs, Nhid hidden nodes and Nout outputs.

See also:  - init

inputs
- inputs

Returns a pointer to the receivers list of input Neurons.

outputs
- outputs

Returns a pointer to the receivers list of output Neurons.