Quantization Error Power Matlab
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Quantization Error Using Matlab
Compute Quantization Error On this page Uniformly Distributed Random Signal Fix: Round Towards Zero. Floor: Round Towards Minus Infinity. Ceil: Round Towards Plus Infinity.
Matlab Code For Quantization Of Sine Wave
Round: Round to Nearest. In a Tie, Round to Largest Magnitude. Convergent: Round to Nearest. In a Tie, Round to Even. Comparison of Nearest vs. Convergent Plot Helper Function Compute Quantization ErrorOpen Script This example shows how to compute and compare the statistics of the signal quantization error when using quantization error formula various rounding methods. First, a random signal is created that spans the range of the quantizer. Next, the signal is quantized, respectively, with rounding methods 'fix', 'floor', 'ceil', 'nearest', and 'convergent', and the statistics of the signal are estimated. The theoretical probability density function of the quantization error will be computed with ERRPDF, the theoretical mean of the quantization error will be computed with ERRMEAN, and the theoretical variance of the quantization error will be computed with ERRVAR. Uniformly Distributed Random SignalFirst we create a uniformly distributed random signal that spans the domain -1 to 1 of the fixed-point quantizers that we will look at.q = quantizer([8 7]); r = realmax(q); u = r*(2*rand(50000,1) - 1); % Uniformly distributed (-1,1) xi=linspace(-2*eps(q),2*eps(q),256); Fix: Round Towards Zero.Notice that with 'fix' rounding, the probability density function is twice as wide as the others. For this reason, the variance is four t
Επιλέξτε τη γλώσσα σας. Κλείσιμο Μάθετε περισσότερα View this message in English Το YouTube εμφανίζεται στα Ελληνικά. Μπορείτε να αλλάξετε αυτή την προτίμηση παρακάτω. Learn more matlab quantizer You're viewing YouTube in Greek. You can change quantization error definition this preference below. Κλείσιμο Ναι, θέλω να τη κρατήσω Αναίρεση Κλείσιμο Αυτό το quantization in matlab code βίντεο δεν είναι διαθέσιμο. Ουρά παρακολούθησηςΟυράΟυρά παρακολούθησηςΟυρά Κατάργηση όλωνΑποσύνδεση Φόρτωση... Ουρά παρακολούθησης Ουρά __count__/__total__ Analysis of Quantization Error Barry Van https://www.mathworks.com/help/fixedpoint/ug/compute-quantization-error.html Veen ΕγγραφήΕγγραφήκατεΚατάργηση εγγραφής10.60110 χιλ. Φόρτωση... Φόρτωση... Σε λειτουργία... Προσθήκη σε... Θέλετε να το δείτε ξανά αργότερα; Συνδεθείτε για να προσθέσετε το βίντεο σε playlist. Σύνδεση Κοινή χρήση Περισσότερα Αναφορά Θέλετε να αναφέρετε το βίντεο; Συνδεθείτε για να αναφέρετε ακατάλληλο περιεχόμενο. Σύνδεση https://www.youtube.com/watch?v=RxHNQLLsnVc Μεταγραφή Στατιστικά στοιχεία 9.159 προβολές 45 Σας αρέσει αυτό το βίντεο; Συνδεθείτε για να μετρήσει η άποψή σας. Σύνδεση 46 1 Δεν σας αρέσει αυτό το βίντεο; Συνδεθείτε για να μετρήσει η άποψή σας. Σύνδεση 2 Φόρτωση... Φόρτωση... Μεταγραφή Δεν ήταν δυνατή η φόρτωση της διαδραστικής μεταγραφής. Φόρτωση... Φόρτωση... Η δυνατότητα αξιολόγησης είναι διαθέσιμη όταν το βίντεο είναι ενοικιασμένο. Αυτή η λειτουργία δεν είναι διαθέσιμη αυτήν τη στιγμή. Δοκιμάστε ξανά αργότερα. Δημοσιεύτηκε στις 31 Δεκ 2012http://AllSignalProcessing.com for more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files.Modeling quantization error as uncorrelated noise. Signal to quantization noise ratio as a function of the number of bits used to represent the signal. Κατηγορία Εκπαίδευση Άδεια Τυπική άδεια YouTube Εμφάν
19, 2007 In problem 4.37 of DSP-Proakis [1], the task is to analyze the total harmonic distortion in quantized sinusoidal, where . My http://www.dsplog.com/2007/03/19/signal-to-quantization-noise-in-quantized-sinusoidal/ take: As detailed in the previous problem (4.36 in DSP-Proakis [1]), due http://www.edaboard.com/thread186844.html to imperfections in practical generation of sinusoidals, apart from the power at the desired frequency, there will be non-zero power for other frequency components as well. This undesirable spurious power typically measured as,total harmonic distortion (THD) is: where and . Note that this definition is different from the quantization error definition provided from [3] - "Total harmonic distortion (THD) is the ratio of the rms value of the fundamental signal to the mean value of the root-sum-square of its harmonics (generally, only the first 5 harmonics are significant)". The definition provided from [1] can be considered as the the signal to quantization noise ratio (SQNR) where the quantization noise includes the quantization error matlab noise power at the harmonics of the desired frequency as well as the noise in other frequency components in . Using bits for quantization, the signal range of 2 units is divided into steps i.e each step is of range units. The original samples of are rounded (quantized) towards the nearest bin location i.e. the quantized signal is . The error due to quantization is . In an article from Analog Devices[2], the author has mentioned that - "quantization error for any ac signal which spans more than a few LSBs can be approximated by an uncorrelated sawtooth waveform". The error signal lies uniformly in the range and the root mean square value of the error signal is . (For details refer Eq 9.2.7. Section 9.2.3 in [1]). The root mean square value of the signal sine wave, . Summarizing, the signal to quantization noise ratio (SQNR) in decibels is: . With this mathematical analysis as a background, let us move on to obtaining the results from quick MATLAB simulations with levels. b = 8;x = sin(2*pi*[0:1/50:1]); xq
Help Rules Groups Blogs What's New? Teardown Videos Datasheets Advanced Search Forum Digital Design and Embedded Programming Digital Signal Processing [SOLVED] SNR of a Quantized Signal using FFT + Post New Thread Results 1 to 10 of 10 SNR of a Quantized Signal using FFT LinkBack LinkBack URL About LinkBacks Thread Tools Show Printable Version Download This Thread Subscribe to this Thread… Search Thread Advanced Search 2nd September 2010,20:21 #1 iffe Newbie level 4 Join Date Sep 2010 Posts 6 Helped 0 / 0 Points 436 Level 4 SNR of a Quantized Signal using FFT Hi all, I have a problem in the calculation of SNR. Sine wave is quantized and then I have calculated its SNR using FFT. The coherence condition with windowing as well is implemented to avoid leakage in the adjacent frequency bins. I am unable to calculate the SNR accurately with different resolution of quantizer (ADC). If I use a standard formula for quantization noise power (Q^2 / 12), the SNR corresponds with the theoretical formula of SNR (SNR = 6.02*NoOfBits + 1.76) but when I try to use my own calculated noise power, the SNR does not corresponds with the theoretical formula with different resolution. I think, I am not calculating the noise power in the correct way. I have considered the noise spectrum starting from 2nd bin to input bandwidth. By the way I am using the formula of SNR = 10*log10(RMS_of_Signal/Mean_of_RSS_of_Noise) Please help. /Iffe 2nd September 2010,20:21 2nd September 2010,21:49 #2 JoannesPaulus Advanced Member level 3 Join Date Mar 2008 Location USA Posts 773 Helped 226 / 226 Points 7,235 Level 20 Re: SNR of a Quantized Signal using FFT The signal power should be calculated as: Code: sig_pwr=sum(X(bin_start:bin_end).*conj(X(bin_start:bin_end))); where X is the DFT of your signal, bin_start is the first bin of your DFT containing signal power, bin_end is the last bin containing signal power (for example, if you use a window that spreads the signal power across 7 bins and the center frequency is at, say, bin 191, bin_start=188; bin_end=194;). The noise power is calculated the same way but skipping the signal bins. M