mirdwt                  package:rwt                  R Documentation

_I_n_v_e_r_s_e _R_e_d_u_n_d_a_n_t _D_i_s_c_r_e_t_e _W_a_v_e_l_e_t _T_r_a_n_s_f_o_r_m

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

     Computes the inverse redundant discrete wavelet transform 'x' for
     input signal 'y' using the scaling filter 'h'. (Redundant means
     here that the sub-sampling after each stage of the forward
     transform has been omitted.)

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

     mirdwt(yl, yh, h, L)

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

      yl: Lowpass component

      yh: Highpass components

       h: Scaling filter to be applied

       L: Number of levels in wavelet decomposition. In the case of a
          1D signal, length(yl) must be divisible by 2^L; in the case
          of a 2D signal, the row and the column dimension must be
          divisible by 2^L. If no argument is specified, a full DWT is
          returned for maximal possible L. 

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

     Returns a list with components: 

       x: Finite length 1D or 2D signal

       L: Number of levels in wavelet decomposition

_A_u_t_h_o_r(_s):

     P. Roebuck, roebuck@mdanderson.org

_R_e_f_e_r_e_n_c_e_s:

     ~put references to the literature/web site here ~

_E_x_a_m_p_l_e_s:

     sig <- makesig(SIGNAL.LEOPOLD, 8)
     h <- daubcqf(4)
     L <- 1
     ret.mrdwt <- mrdwt(sig$x, h$h.0, L)
     ret.mirdwt <- mirdwt(ret.mrdwt$yl, ret.mrdwt$yh, h$h.0, ret.mrdwt$L)

