mlp                  package:neural                  R Documentation

_M_L_P _n_e_u_r_a_l _n_e_t_w_o_r_k

_D_e_s_c_r_i_p_t_i_o_n:

     The recalling method of the MLP network which was trained by the
     mlptrain function.

_U_s_a_g_e:

      mlp(inp,weigth,dist,neurons,actfns)

_A_r_g_u_m_e_n_t_s:

     inp: a matrix that contains one input data in each row.

  weigth: the weigths of the network.

    dist: the distortions of the network.

 neurons: a numeric vector with length equals to the number of layers
          in the network, and the ith layer will contains neurons[i]
          neuron.

  actfns: a numeric vector, that contains the numeric codes of the
          activation functions. The length of the vector must be the
          same as the length of the neurons vector, and each element of
          the vector must be between 1-4. The possible numeric codes
          are the following: 1: Logistic function 2: Hyperbolic tangent
          function 3: Gauss function 4: Identical function.

_D_e_t_a_i_l_s:

     the last four argument is determined by the mlptrain algorithm.

_V_a_l_u_e:

     a matrix that contains the response data of the network, each row
     contains one response.

_S_e_e _A_l_s_o:

     `mlptrain' for training an MLP network, `rbf' and `rbftrain' for
     approximation.

