Class implementing a layer of a neural net - HTML documentation under construction.

Inheritance:

Public Methods

	LayerNet ()
	LayerNet (unsigned num_outputs, unsigned num_inputs, act_func f=sigmoid)
virtual	~LayerNet ()
vect&	compute (vect& vinput)
void	print_weights ()
void	print_out ()
void	print_dim () const
inline unsigned	Read_ninputs () const
inline unsigned	Read_noutputs () const
inline vect&	Read_bias ()
inline vect&	Read_out ()
inline vect&	Read_a ()
inline matrix&	Read_W ()
inline act_func	Read_g ()
inline act_func	Read_dg ()
void	Print_info ()
void	init_weights (double x)
void	init_norm_weights (long seed = 0)
void	load_weights (istream& f)

Protected Fields

static const unsigned	WEIGHT_PRECISION
unsigned	n_inputs
unsigned	n_outputs
matrix	W
vect	bias
vect	out
vect	a
act_func	g
act_func	dg

Protected Methods

act_func

do_deriv (act_func f)

Documentation

The class implements a layer of a neural net.

LayerNet()

LayerNet(unsigned num_outputs, unsigned num_inputs, act_func f=sigmoid)

virtual ~LayerNet()

vect& compute(vect& vinput)

void print_weights()

void print_out()

void print_dim() const

inline unsigned Read_ninputs() const

inline unsigned Read_noutputs() const

inline vect& Read_bias()

inline vect& Read_out()

inline vect& Read_a()

inline matrix& Read_W()

inline act_func Read_g()

inline act_func Read_dg()

void Print_info()

void init_weights(double x)

void init_norm_weights(long seed = 0)

void load_weights(istream& f)

static const unsigned WEIGHT_PRECISION

unsigned n_inputs

unsigned n_outputs

matrix W

vect bias

vect out

vect a

act_func g

act_func dg

act_func do_deriv(act_func f)

Direct child classes:

LayerNetTrain

Friends:

class Learning
class GradientDescent
class MomentumDescent

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