Impulsive Noise Meter: [dB]=Pa_to_dB(p, ref) - File Exchange

Code covered by the BSD License

Highlights from
Impulsive Noise Meter

choosebox(varargin) CHOOSEBOX Two-listed item selection dialog box.
findjobj(container,varargin) findjobj Find java objects contained within a specified java container or Matlab GUI handle
tableGUI(varargin) TABLEGUI - Spreadsheet like display and edition of a generic 2D array. By generic it is
ACdsgn(Fs)
ArgStruct=parseArgs(args,ArgS... Helper function for parsing varargin.
Main_Sound % Main_Sound: Main Program for the Impulsive Noise Meter and outputs a table of impulsive noise metrics
[A2, A_str, real_digitsL, rea... % m_round: Rounds an array to a specified number of significant digits or a specified digits place: significant figures, sigfigs
[A2, A_str, real_digitsL, rea... % pow10_round: Round a numeric array to a Specified Digits Place
[A2, A_str, real_digitsL, rea... % sd_round: Rounds an array to a specified number of Significant Digits, significant figures, digits of precision
[B, A]=Nth_octdsgn(Fs, Fc, N,...
[C, y, X, n, p, error1]=LMS_t... % LMS_trim: Randomly trims the input data arrays and combinataions of data points.
[Fsn, p, q, errors]=get_p_q2(...
[LMSout, blms, Rsq, error1]=L... % LMTSregor: Estimates the best fit line through tthe origin using a random trimming and least median squares
[LeqA, LeqA8, LeqC, LeqC8, Le... % Leq_all_calc: Calculates levels and peaks for A, C, and linear weighting
[Pa]=dB_to_Pa(dB, ref) % written by Edwdard Zechmann
[SP, vibs, Fs_SP, Fs_vibs, de... % data_loader2: Loads data specified as sound or vibrations and further specified as data, time increment or sampling rate
[SP2, mean_array2, mean1, arr... % sub_mean: Removes the running average from a time record given a sampling rate and high pass cutoff frequency.
[SP2, mean_array2]=sub_mean(S... % sub_mean: Removes the running average from a time record given a sampling rate and high pass cutoff frequency.
[SP_local_max2, indices2, SP_... % localpeaks: Finds impulsive peaks and returns the amplitudes and indices
[SP_maxa, index_maxa]=peak_in... % peak_index: Finds the highest data point centered about center_bin
[a, at2, at1]=A_duration(p, F... % A_duration: Calculates the A-duration for impulsive noise
[a, b_mil, c, d, ee]=abcd_dur... % abcd_durations: Calculates the A, B, C, and D durations for impulsive noise
[alpha]=t_alpha(t, nu) % t_alpha: cumulative probability function of the t-distribution,
[b, pp, sf, Lpt2, Lpt1, Basel... % B_mil_1474D_duration: Calculates the B-duration according to MIL-STD-1474D Requirement 4.
[b_min, b, p2]=E_duration(p, ... % E_duration: Calculates the E-duration for impulsive noise
[buf2, num_files_not_empty]=s... % splat_cell: Returns a row vector of numbers containng all of the numbers in a cell array
[bz, az]=bessel_digital(Fs, F... % bessel_digital: creates a digital low pass bessel filter of order n
[c, c2, error_cond, t_a]=C_du... % C_duration: Calculates the C-duration for impulsive noise
[d, ddd, ee, tau_fit, y2, y4]... % D_duration: Calculates the D-duration for impulsive noise
[dB]=Pa_to_dB(p, ref)
[fc_out, SP_levels, SP_peak_l... % Nth_oct_time_filter2: Calculates the Nth octave center frequencies, sound levels, peak levels, and time records
[fid, mean_vals, max_num_chan... % print_channel_stats: Print the ststistics for each channel for the impulsive sound table
[fid]=print_outliers_indices(... % written by Edward L. Zechmann 11 January 2009
[fid]=print_overall_stats(fid... % print_overall_stats: Print the overall statistics for the impulsive sound table
[filename_base, ext]=file_ext... % file_extension: separates a filename and path from the file extension
[gm]=geomean2(y, dim) % geomean2: Calculates the geometric mean
[h, h2, indices2]=plotpeaks(S... % plotpeaks: finds peaks, plots peaks, then outputs impulsive noise metrics
[h, h2, wb_th_array]=plot_snd... % plot_snd_vibs(: plots sound and vibrations data in the time domain
[interval, error]=t_confidenc... % t_confidence_interval: One or two sided confidence interval of standard error with t distribution
[m2]=geospace(a, b, n, flag) % geospace: caculates a geometric sequence or psuedogeometric sequence from a to b with n elements
[ma,mi]=findextrema(a) FINDEXTREMA - finds minima and maxima of data
[maix, epts]=threshold_bin_pe...
[metrics, metric_str, metric_... % snd_peak_metrics: Calculates impulsive sound metrics including Nth octave band Leqs and peak levels
[ndraw, count, count2, error]... % rand_int: Quckly generates n random integers from a to b integer
[num_samples_ca, s]=num_impul... % num_impulsive_samples: Counts the number of impulsive noise samples
[nums, matches]=find_nums(str... % find_nums: Finds floating point complex, real, integer, and currency (dollars) numbers in a string
[out]=print_data_loader_confi... % print_data_loader_configuration_table: Prints the variable configuration to a table
[pc_ix, pc_int]=find_previous... % find_previous_crossing: finds previous crossing above or below p_value
[peak_indices, gp, Pa_peak, L... % peak_ix: Locates peaks for acoustic impulsive noise
[pfq]=genHyper(a,b,z,lnpfq,ix... function [pfq]=genHyper(a,b,z,lnpfq,ix,nsigfig)
[prms]=rms_val(p, dim) % rms_val: Calculates the rms value along a specific dimension
[ptsa, nptsa, rt_stats, other... % data_outliers: Determine the outliers and return descriptive statistics
[res,raw]=fastmcd(data,option... version 22/12/2000, revised 19/01/2001,
[rt, pz_ix, pl_ix, ph_ix]=ris...
[s, round_kind, round_digits]... % Impulsive_Noise_Meter: Loads sound time records, finds Peaks, calculates impulsive sound metrics
[s]=calc_diff_metrics(s, diff... % calc_diff_metrics: Calculates the differences in metrics between pairs of channels: Impulsive Noise Meter
[sf, sf2, ctime, spa, mpa, er... % B_Duration_second_flucts: Calculates the secondary fluctuations for the B-duration of impulsive noise
[t_SP_rs, SP_rs]=resample_plo... % resample_plot: Resamples a plot to 10000 data points using the max and%min from each bin
[t_out, T_out, error1_out, er... % inverse cumulative probability function, t-distribution
[varargout]=convert_double(va... % This program converts the inputs into double precision arrays. Then
[y, t]=analytic_impulse(Fs, f... % analytic_impulse: Impulsive noise with known peak level, frequency, duration
[y, x, a]=match_height_and_sl... % match_height_and_slopes2: creates a quartic with specifed height and slope at the end points.
[y2, num_settle_pts, settling... % filter_settling_data: Creates data to append to a time record for settling a filter
[y2]=remove_filter_settling_d... % remove_filter_settling_data: removes data added to time records to settle the filter
[yAC, errors]=ACweight_time_f... % ACweight_time_filter: Applies an A or C weighting time filter to a sound recording
[y]=moving(x,m,fun) MOVING will compute moving averages of order n (best taken as odd)
[y_out, b, a]=bessel_antialia... % bessel_antialias: applies an antialiasing digital Bessel filter
[y_out, t_out, b, a]=bessel_d... % bessel_down_sample: applies an antialiasing digital Bessel filter
[y_out, x_out, y_in]=resample... % resample_interp3: resamples using interp1 with additional options
[ytick_m, YTickLabel1, ytick_... % fix_YTick: Sets appropriate Y-Tick values for small plots
estimatenoise(X,varargin) estimatenoise: additive noise estimation from a time series
fastlts(x,y,options)
func_threshold(I) Compute an optimal threshold for seperating the data into two classes [1].
gp=peak_threshhold_function2(... % peak_threshhold_function2: Calculates a threshold for finding peaks
h=subaxis(varargin) SUBAXIS Create axes in tiled positions. (just like subplot)
kurtosis2(x, dimension) % This program calculates the kurtosis.
loc=LMSloc(X)
make_summary_impls_stats_tabl... % make_summary_impls_stats_table: Makes a summary table of the output of the Impulsive_Noise_Meter; Impulse, Impulsive, Noise, Sound, Meter
maximize(hFig) MAXIMIZE Maximize a figure window to fill the entire screen
nth_freq_band(N, min_f, max_f... % nth_freq_band: Calculates the 1/nth octave frequency bands center, lower, and upper bandedge limits
peakfinder(x0, thresh, extrem... PEAKFINDER Noise tolerant fast peak finding algorithm
psuedo_box(h_array)
save_a_plot2_audiological(a, ... % save_a_plot2_audiological: Saves current figure to specified image type.
wsmooth(z,x,y,L) WSMOOTH 1D and 2D robust smoothing.
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from Impulsive Noise Meter by Edward Zechmann
Calculates Impulsive noise metrics for hazardous acoustic noise assessent

[dB]=Pa_to_dB(p, ref)

function [dB]=Pa_to_dB(p, ref)
% % 
% % 
% % 
% % written by Edwdard Zechmann 
% % 
% % date      3 September   2009
% % 
% % modified 23 March       2010
% % 

if nargin < 1 
    p=1;
end

if nargin < 2 
    ref=0.00002;
end


dB=20.*log10(abs(p)./ref);

Highlights from Impulsive Noise Meter

Highlights from
Impulsive Noise Meter