# Begin VHDL Code Generation for 'hdlcoderFocCurrentFixptHdl'. # Generating new validation model: gm_hdlcoderFocCurrentFixptHdl_vnl. # Rendering DUT with optimization related changes (IO, Area, Pipelining). # Begin model generation 'gm_hdlcoderFocCurrentFixptHdl'. # Working on the model 'hdlcoderFocCurrentFixptHdl'. # Begin compilation of the model 'hdlcoderFocCurrentFixptHdl'. # Running HDL checks on the model 'hdlcoderFocCurrentFixptHdl'. # Using the config set for model hdlcoderFocCurrentFixptHdl for HDL code generation parameters. To avoid run-time errors, simulate the design with the test bench.# Generating HDL for 'hdlcoderFocCurrentFixptHdl/FOC_Current_Control'. Xlabel( 'coefficient #') ylabel( 'coefficient value') Xlabel( 'time index') ylabel( 'signal value') Title( 'System Identification of an FIR filter') = mlhdlc_lms_fcn(step(hSrc), step(hDesiredSrc). Rng( 'default') % always default to known stateĭ = step(hfilt, x) + 0.01*randn(1000,1) % desired signal Hfilt = dsp.FIRFilter % System to be identified % Copyright 2011-2022 The MathWorks, Inc. % returns an adaptive FIR filter System object, HLMS, that computes the % filtered output, filter error, and the filter weights for a given input % and desired signal using the Least MeanSquares (LMS) algorithm. The MATLAB function is modular and uses functions: Updated_weight = correction_factor + filter_coeff % NOTE: To instruct MATLAB Coder to compile an external function, % add the following compilation directive or pragma to the function code %#codegenĬorrection_factor = delayed_signal. % This function updates the adaptive filter weights based on LMS algorithm % Copyright 2007-2022 The MathWorks, Inc. ĭelayed_signal, filter_coeff, reset_weights) The output includes current input % NOTE: To instruct MATLAB Coder to compile an external function, % add the following compilation directive or pragma to the function code %#codegen persistent u_d įunction weights = update_weight_fcn(step_size, err_sig. % The Tapped Delay function delays its input by the specified number % of sample periods, and outputs all the delayed versions in a vector % form.

% The ideal way to code this generically for any length of 'u' is to use % recursion but it is not currently supported by MATLAB Coder % NOTE: To instruct MATLAB Coder to compile an external function, % add the following compilation directive or pragma to the function code %#codegen % This implementation is hardwired for a 40tap filter.įunction tap_delay = mtapped_delay_fcn(input) % A tree is more efficient as it results in % delay of log2(N) instead of a delay of N delay % This implementation shows how to explicitly implement the vector sum in % a tree shape to enable hardware optimizations. %Implement the 'sum' function without a for-loop % y = sum(u) % The loop based implementation of 'sum' function is not ideal for % HDL generation and results in a longer critical path. Updated_weight = update_weight_fcn(step_size, esig, delayed_signal. % Update Weights: Call 'update_weight_fcn' function on MATLAB path to % calculate the new weights % Call treesum function on matlab path to sum up the resultsįiltered_signal = mtreesum_fcn(weight_applied) % register filter coefficients persistent filter_coeff Įnd % Variable Filter: Call 'mtapped_delay_fcn' function on path to create % 40-step tapped delayĭelayed_signal = mtapped_delay_fcn(input) The coefficients/weights of the filter % are updated(adapted) in real-time based on 'input' and 'err_sig'.

% 'desired': The signal from Pilot's Mic which includes % original music signal and the noise signal % 'err_sig': The difference between the 'desired' and the filtered 'input' % It represents the estimated music signal (output of this block) % % The LMS filter is trying to retrieve the original music signal('err_sig') % from Pilot's Mic by filtering the Exterior Mic's signal and using it to % cancel the noise in Pilot's Mic. % 'input' : The signal from Exterior Mic which records the ambient noise.

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