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: ce_FindRipples.m
    path of file: ./repos/CellExplorer/calc_CellMetrics
    
    the code of the file until where you have to start completion: function [ripples] = ce_FindRipples(varargin)
%FindRipples - Find hippocampal ripples (100~200Hz oscillations).
%
% USAGE
%    ripples = ce_FindRipples(session); % This requires the ripple channel defined in the session struct: session.channelTags.Ripple.channels = 1;
%       You still have to define processing parameters 
%    OR
%    ripples = ce_FindRipples(lfp.data,lfp.timestamps,<options>)
%    OR
%    ripples = ce_FindRipples(basepath,channel,<options>)
%
%    Ripples are detected using the normalized squared signal (NSS) by
%    thresholding the baseline, merging neighboring events, thresholding
%    the peaks, and discarding events with excessive duration.
%    Thresholds are computed as multiples of the standard deviation of
%    the NSS. Alternatively, one can use explicit values, typically obtained
%    from a previous call.  The estimated EMG can be used as an additional
%    exclusion criteria
%
% INPUTS - note these are NOT name-value pairs... just raw values

%    lfp            unfiltered LFP (one channel) to use

    
function [ripples] = ce_FindRipples(varargin)
%FindRipples - Find hippocampal ripples (100~200Hz oscillations).
%
% USAGE
%    ripples = ce_FindRipples(session); % This requires the ripple channel defined in the session struct: session.channelTags.Ripple.channels = 1;
%       You still have to define processing parameters 
%    OR
%    ripples = ce_FindRipples(lfp.data,lfp.timestamps,<options>)
%    OR
%    ripples = ce_FindRipples(basepath,channel,<options>)
%
%    Ripples are detected using the normalized squared signal (NSS) by
%    thresholding the baseline, merging neighboring events, thresholding
%    the peaks, and discarding events with excessive duration.
%    Thresholds are computed as multiples of the standard deviation of
%    the NSS. Alternatively, one can use explicit values, typically obtained
%    from a previous call.  The estimated EMG can be used as an additional
%    exclusion criteria
%
% INPUTS - note these are NOT name-value pairs... just raw values

%    lfp            unfiltered LFP (one channel) to use
%	 timestamps	    timestamps to match filtered variable
%    <options>      optional list of property-value pairs (see tables below)
%
%    OR
%
%    basepath       path to a single session to run findRipples on
%    channel      	Ripple channel to use for detection (1-indexed ala Matlab)
%
%    =========================================================================
%     Properties    Values
%    -------------------------------------------------------------------------
%     'thresholds'  thresholds for ripple beginning/end