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: FIGFilter.m
    path of file: ./repos/libDirectional/lib/filters
    
    the code of the file until where you have to start completion: classdef FIGFilter < AbstractCircularFilter & AbstractGridFilter
    % Implementation of the Fourier-interpreted grid filter.
    % see Florian Pfaff, Kailai Li, and Uwe D. Hanebeck,
    % Fourier Filter
    
function predictIdentity(this, dSys)
            % Predicts assuming identity system model, i.e.,
            % x(k+1) = x(k) + w(k)    mod 2pi,
            % where w(k) is additive noise given by dSys.
            %
            % Parameters:
            %   dSys (AbstractCircularDistribution or samples on grid)
            %       distribution of additive noise or samples on a grid. If
            %       values on a grid are given, take care that they are
            %       not rooted yet. Take care that if
            %       linspace(0,2*pi,noCoeffs) is used, that the last grid
            %       point has to be discarded. For example
            %       xvals=0:2*pi/noCoeffs:2*pi-2*pi/noCoeffs;
            assert(isa(dSys, 'AbstractCircularDistribution'))
            % If a distribution on a circle is given, use Hadamard
            % product approach
            if ~isa(dSys, 'FIGDistribution')
                warning('Predict:automaticConversion', ...
                    'dSys is not a FIGDistribution. Transforming with a number of coefficients that is equal to that of the filter. For non-varying noises, transforming once is much more efficient and should be preferred.');
                dSys = FIGDistribution.fromDistribution(dSys, numel(this.gd.gridValues), this.gd.enforcePdfNonnegative);
            end