You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: DEM_demo_convolution.m
    path of file: ./repos/spm/toolbox/DEM
    
    the code of the file until where you have to start completion: function DEM_demo_convolution
% DEM demo for linear deconvolution:  This demo considers the deconvolution
% of the responses of a single-input-multiple output input-state-output
% model (DCM) to disclose the input or causes.  It focuses on estimating the
% causes and hidden states: The notes provide a comparative evaluation with 
% extended Kalman filtering (see script after return).
 
 
% get a simple convolution model
%==========================================================================
M       = spm_DEM_M('convolution model');
M(1).V  = exp(8);                             % error precision
M(1).W  = exp(8);                             % error precision

    
function DEM_demo_convolution
% DEM demo for linear deconvolution:  This demo considers the deconvolution
% of the responses of a single-input-multiple output input-state-output
% model (DCM) to disclose the input or causes.  It focuses on estimating the
% causes and hidden states: The notes provide a comparative evaluation with 
% extended Kalman filtering (see script after return).
 
 
% get a simple convolution model
%==========================================================================
M       = spm_DEM_M('convolution model');
M(1).V  = exp(8);                             % error precision
M(1).W  = exp(8);                             % error precision
 
% and generate data
%==========================================================================
N       = 32;                                 % length of data sequence
U       = exp(-([1:N] - 12).^2/(2.^2));       % this is the Gaussian cause;
DEM     = spm_DEM_generate(M,U,{},{[] 16},{16});
 
% invert model
%==========================================================================
DEM     = spm_DEM(DEM);
 
% overlay true values
%--------------------------------------------------------------------------
spm_DEM_qU(DEM.qU,DEM.pU)


return
 
 
% explore dimensions (n)
%==========================================================================
for i = 1:8
    DEM.M(1).E.n = i;
    DEM.M(1).E.d = 3;
    
    D{i}   = spm_DEM(DEM);
    F(i)   = D{i}.F;
    Sx(i)  = sum(sum((D{i}.qU.x{1} - DEM.pU.x{1}).^2));
    Sv(i)  = sum(sum((D{i}.qU.v{2} - DEM.pU.v{2}).^2));
end