+++ Changes +++
+ duobinary_target now supports memoryless decoding (FFE targets DB response without MLSE) + PAMmapper.quantize now supports custom constellations for quantization + Added a new folder 'Documentations' for pdfs, slides, etc. + Added new FSO evaluation scripts in projects/FSO transmission/Evaluation Scripts + Added ffe_db (rudimentary module, not important anymore)
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magf
211
Functions/EQ_structures/ffe_db.m
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211
Functions/EQ_structures/ffe_db.m
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function [ffe_results] = ffe_db(eq_, M, rx_signal, tx_symbols, tx_bits, options)
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% FFE Processes signals through FFE equalizer
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%
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% Inputs:
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% eq_ - Equalizer object
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% M - Modulation order
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% rx_signal - Received signal
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% tx_symbols - Transmitted symbols
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% tx_bits - Transmitted bits
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% options - Optional parameters
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%
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% Outputs:
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% ffe_results - Results from FFE processing
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arguments
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eq_
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M
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rx_signal
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tx_symbols
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tx_bits
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options.db_target = 0;
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options.precode_mode db_mode
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options.showAnalysis = 0;
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options.eth_style_symbol_mapping = 0;
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options.postFFE = [];
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options.database = [];
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end
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%% Process signals through equalizer
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% FFE or VNLE
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if options.db_target
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tx_symbols_ref = Duobinary().encode(tx_symbols);
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db_ref_constellation = unique(tx_symbols_ref.signal);
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[eq_signal_sd, eq_noise] = eq_.process(rx_signal, tx_symbols_ref);
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else
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[eq_signal_sd, eq_noise] = eq_.process(rx_signal, tx_symbols);
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end
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% Apply post-FFE if provided
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if ~isempty(options.postFFE)
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tic
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[eq_signal_sd, eq_noise] = options.postFFE.process(eq_signal_sd, tx_symbols);
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toc
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end
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try
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ch_coefficients = arburg(eq_noise.signal,1);
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channel_alpha = ch_coefficients(2);
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end
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% Hard decision on FFE output
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if options.db_target
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eq_signal_hd = PAMmapper(M, 0).quantize(eq_signal_sd,'custom_const',db_ref_constellation.');
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else
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eq_signal_hd = PAMmapper(M, 0).quantize(eq_signal_sd);
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end
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if options.db_target
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eq_signal_hd = Duobinary().decode(eq_signal_hd);
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tx_symbols = Duobinary().encode(tx_symbols);
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tx_symbols = Duobinary().decode(tx_symbols);
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end
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%% Calculate BER based on precoding mode
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[bits, errors, ber, error_pos, errors_precoded, ber_precoded] = calculateBER(eq_signal_hd, tx_symbols, tx_bits, options.precode_mode, M, options.eth_style_symbol_mapping);
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%% Calculate performance metrics
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[snr, snr_lvl] = calc_snr(tx_symbols.signal, eq_noise.signal);
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% [gmi] = calc_air(eq_signal_sd, tx_symbols, "skip_front", 10000, "skip_end", 10000);
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[gmi] = calc_ngmi(eq_signal_sd,tx_symbols);
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gmi = max(gmi,0);
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air = tx_symbols.fs .* floor(log2(double(M))*10)/10 .* gmi ./ log2(double(M));
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[evm_total, evm_lvl] = calc_evm(eq_signal_sd, tx_symbols);
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[std_total, std_lvl] = calc_std(eq_signal_sd, tx_symbols);
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[std_rxraw_total, std_rxraw_lvl] = calc_std(rx_signal.resample("fs_out", tx_symbols.fs), tx_symbols);
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%% Display analysis if requested
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if options.showAnalysis
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displayAnalysis(eq_noise, eq_signal_sd, rx_signal, eq_, tx_symbols, M, options.postFFE);
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end
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%% Prepare output structure
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% Determine postFFE order
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if ~isempty(options.postFFE)
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npostFFE = options.postFFE.order;
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else
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npostFFE = 0;
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end
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% Create FFE results structure
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ffe_results = struct();
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try
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eq_.e = [];
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eq_.e2 = [];
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eq_.e3 = [];
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eq_.b = [];
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eq_.b2 = [];
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eq_.b3 = [];
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end
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ffe_results.config = Equalizerstruct();
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ffe_results.config.eq = jsonencode(eq_);
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ffe_results.config.equalizer_structure = int32(equalizer_structure.ffe);
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ffe_results.config.comment = 'function: ffe';
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ffe_results.metrics = Metricstruct;
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ffe_results.metrics.result_id = NaN;
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ffe_results.metrics.run_id = NaN;
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ffe_results.metrics.eqParam_id = NaN;
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ffe_results.metrics.date_of_processing = datetime('now');
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ffe_results.metrics.BER = ber;
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ffe_results.metrics.numBits = bits;
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ffe_results.metrics.numBitErr = errors;
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ffe_results.metrics.BER_precoded = ber_precoded;
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ffe_results.metrics.numBitErr_precoded = errors_precoded;
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ffe_results.metrics.SNR = snr;
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ffe_results.metrics.SNR_level = snr_lvl;
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ffe_results.metrics.STD = std_total;
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ffe_results.metrics.STD_level = std_lvl;
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ffe_results.metrics.STDrx = std_rxraw_total;
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ffe_results.metrics.STDrx_level = std_rxraw_lvl;
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ffe_results.metrics.GMI = gmi;
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ffe_results.metrics.AIR = air;
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ffe_results.metrics.EVM = evm_total;
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ffe_results.metrics.EVM_level = evm_lvl;
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ffe_results.metrics.Alpha = channel_alpha;
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end
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%% Helper Functions
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function [bits, errors, ber, error_pos, errors_precoded, ber_precoded] = calculateBER(eq_signal_hd, tx_symbols, tx_bits, precode_mode, M, eth_style)
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% Calculate BER based on precoding mode
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mapper = PAMmapper(M, 0, "eth_style", eth_style);
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switch precode_mode
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case db_mode.no_db
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% TX Data is not precoded
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% A) Emulate diff precoding
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eq_signal_hd_precoded = Duobinary().encode(eq_signal_hd, "M", M);
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eq_signal_hd_precoded = Duobinary().decode(eq_signal_hd_precoded, "M", M);
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tx_symbols_precoded = Duobinary().encode(tx_symbols);
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tx_symbols_precoded = Duobinary().decode(tx_symbols_precoded);
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tx_bits_precoded = mapper.demap(tx_symbols_precoded);
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rx_bits = mapper.demap(eq_signal_hd_precoded);
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[~, errors_precoded, ber_precoded, ~] = calc_ber(rx_bits.signal, tx_bits_precoded.signal, "skip_front", 10, "skip_end", 10, "returnErrorLocation", 1);
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% B) Just determine BER
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rx_bits = mapper.demap(eq_signal_hd);
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tx_bits = mapper.demap(tx_symbols);
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[bits, errors, ber, error_pos] = calc_ber(rx_bits.signal, tx_bits.signal, "skip_front", 10, "skip_end", 10, "returnErrorLocation", 1);
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case db_mode.db_precoded
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% Data is precoded on TX side
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% A) Decode at Rx if no DB targeting was applied
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eq_signal_hd_decoded = Duobinary().encode(eq_signal_hd, "M", M);
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eq_signal_hd_decoded = Duobinary().decode(eq_signal_hd_decoded, "M", M);
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rx_bits_decoded = mapper.demap(eq_signal_hd_decoded);
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[~, errors_precoded, ber_precoded, ~] = calc_ber(rx_bits_decoded.signal, tx_bits.signal, "skip_front", 10, "skip_end", 10, "returnErrorLocation", 1);
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% B) Omit the Coding by comparing with demapped TX symbol sequence
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tx_bits_demapped = mapper.demap(tx_symbols);
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rx_bits = mapper.demap(eq_signal_hd);
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[bits, errors, ber, error_pos] = calc_ber(rx_bits.signal, tx_bits_demapped.signal, "skip_front", 10, "skip_end", 10, "returnErrorLocation", 1);
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end
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end
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function displayAnalysis(eq_noise, eq_signal_sd, rx_signal, eq_, tx_symbols, M, postFFE)
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% Display analysis plots and metrics
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% Initialize figure handles
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% Corrected line - added tx_symbols as second positional argument
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% showLevelScatter(rx_signal.resample("fs_out", tx_symbols.fs), tx_symbols, "fignum", 100);
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warning off
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showLevelScatter(eq_signal_sd, tx_symbols, "fignum", 101);
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figure(gcf);hold on; plot(((1:length(eq_noise.signal)) / eq_noise.fs) * 1e6,movmean(eq_noise.signal,2000,1), 'LineWidth',3,'Color','black')
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warning on
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showLevelHistogram(eq_signal_sd, tx_symbols, "fignum", 102);
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showEQNoisePSD(eq_noise, "fignum", 103, "displayname", 'Residual Noise after FFE');
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% Figure 2: Post-FFE coefficients (if available)
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if ~isempty(postFFE)
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showEQcoefficients('n1', postFFE.e, "displayname", 'Coefficients', 'fignum', 104);
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end
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try
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figure(339);hold on
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showEQfilter(eq_.e, eq_signal_sd.fs.*2,"displayname",'training','fignum',339);
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% showEQfilter(eq_.e, eq_signal_sd.fs.*2,"displayname",'dec. directed','fignum',339);
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legend on
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end
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% try
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% figure(240); hold on; plot(pow2db(movmean(eq_.debug_struct.error_tr',100)));ylim([-30,3]);title('error training');
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%
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% figure(241); hold on; plot(pow2db(movmean(eq_.debug_struct.update_tr',100)));title('update step training');
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%
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% figure(242); hold on; plot(pow2db(movmean(eq_.debug_struct.update',1000)));title('update step dd');
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% end
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eq_signal_sd.eye(eq_signal_sd.fs,M,"displayname",'Eye','fignum',105);
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end
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