#FREAC BAD SAMPLING RATE CODE#

However, a 12-bit resolution ADC system has at best a signal-to-noise ratio of only 74dB, so while it would be able to capture sound at some level, the background hiss will be noticeable. So 16-bits is enough resolution to capture good quality audio, at least in terms of dynamic range. At 16-bit resolution, the ratio between the loudest expressible signal sound and the 'noise level' of the inherent quantization noise, would be 98dB - painfully loud. While dB is a general-purpose ratio unit, for audio applications it is related to the Sound Pressure Level or loudness of a sound. There are other noise sources besides quantization error, we just use ENOB to express effective number of bits because quantization error is the one noise source that we can never get rid of. A 16-bit system with 92dB SNR from various noise sources, is effectively comparable to a 15-bit system with noise only from quantization error. We often use this in characterizing the noise floor of an ADC system, where N is the actual number of bits, and ENOB is the 'effective' number of bits. But the built-in ADC is probably adequate for phone-quality speech or music played through tinny cheap speakers.ĭynamic Range expressed as Effective Number of Bits (ENOB) is another way of expressing Signal to Noise Ratio (SNR): Ultimately the easiest thing to do is try it if it's not up to your percieved quality standards, you'll want an external ADC with its own little linear regulator and separate area of the PCB. What that is likely to mean that every power burst from the radio side gets conducted straight into the audio. Since no mention is made of using an external reference voltage, or separate analog power/ground, or a PSRR number, I suspect this is very bad. This is the ability to avoid conducting noise from the power supply into the analog results. There is also a general concern for any ADC on the same chip as digital circuitry: power supply rejection ratio (PSRR). This matters less for audio applications where the DC level can be normalised later, but for other applications it will definitely require calibration. The interpolation filter sample I provided above is FIR and zeros phase filter, which means finite impulse response (i.e., no error propogation and phase distortion).ĭO NOT FORGET to RECONSTRUCT YOUR SIGNAL, or you will overestimate the uncertainty.I agree with Justme's answer that the DNL/INL is quite high, and also call your attention to this sentence:īy default, there are ☖% differences in measured results between chips. To sum up, as long as the band-limited signal is sampled higher than the Nyquist frequency, properly reconstruction (interpolation) can theoretically reduce the uncertainty to a very small amount (which depends on the interpolation filters you designed).

If you forget to interpolate, the uncertainty of x_d is very high!! However, as long as you properly interpolate the x_d, you will obtain the x_r where the uncertainty is much much smaller. % (i,e, here I filterout the freq larger than 2.5(Nyquist rate) * 0.9 = 2.25Hz) % Given known limit band signal, a shorter ratio can enhance SNR by oversampling. % please not the parameter 0.9, ideally should be 1 for Nyquist rate. H = intfilt(analog_fps/digital_fps,4,0.9) X_up = upsample(x_d,analog_fps/digital_fps) X_d = x_s % For basic case, we skip the quantizing here. % x_d = Quantizing(x_s,B,X_m) % A For complete ADC, a quantizing should % Quantizing (abs of input value should not over 1) X_s = downsample(x_a,analog_fps/digital_fps) % add a small high-frequency component as asked. N = downsample(t,analog_fps/digital_fps) T = 0:1/analog_fps: analog_window_time-1/analog_fps

#FREAC BAD SAMPLING RATE CODE#

%% This code simulate the AD/DA processing discussed in Chapter 4.8.3 This sample code sample a simulated 2 Hz analog signal,x_a, (with sampling rate 1500 Hz) to a discrete-time signal,x_d, with 5 Hz sampling rate (nearly Nyquist rate) and then reconstruct this back,x_r. Most of the analyzers forget to reconstruct (interpolate) their sampled signal while analyzing. But, YOU NEED TO RECONSTRUCT THE SAMPLED SIGNAL before the temporal analysis. The main reason is depicted as follows.Īlthough Nyquist-Shannon sampling theorem state that no theoretical reconstruction loss as long as the sampling frequency is twice larger than the bandwidth. In fact, the uncertainty between sampled peaks can be solved by properly designed interpolation (or DAC) as long as the sampling theorem is met. Uncertainty is mostly determined by both the Bandwidth of the signal you sampled (as stated by Marcus Muller) and the sampling frequency. Uncertainty IS NOT determined by the sampling frequency (i.e., 100Hz) only.

Freac bad sampling rate