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In telecommunication, a non-return-to-zero (NRZ) line code is a binary code in which ones are represented by one significant condition, usually a positive voltage, while zeros are represented by some other significant condition, usually a negative voltage, with no other neutral or rest condition. For a given data signaling rate, i.e., bit rate, the NRZ code requires only half the baseband bandwidth required by the Manchester code (the passband bandwidth is the same). The pulses in NRZ have more energy than a return-to-zero (RZ) code, which also has an additional rest state beside the conditions for ones and zeros. When used to represent data in an asynchronous communication scheme, the absence of a neutral state requires other mechanisms for bit synchronization when a separate clock signal is not available. Since NRZ is not inherently a self-clocking signal, some additional synchronization technique must be used for avoiding bit slips; examples of such techniques are a run-length-limited constraint and a parallel synchronization signal. NRZ can refer to any of the following serializer line codes: The NRZ code also can be classified as a polar or non-polar, where polar refers to a mapping to voltages of +V and −V, and non-polar refers to a voltage mapping of +V and 0, for the corresponding binary values of 0 and 1. Unipolar encoding "One" is represented by a DC bias on the transmission line (conventionally positive), while "zero" is represented by the absence of bias – the line at 0 volts or grounded. For this reason it is also known as "on-off keying". In clock language, a "one" transitions to or remains at a biased level on the trailing clock edge of the previous bit, while "zero" transitions to or remains at no bias on the trailing clock edge of the previous bit. Among the disadvantages of unipolar NRZ is that it allows for long series without change, which makes synchronization difficult, although this is not unique to the unipolar case. One solution is to not send bytes without transitions.
[2]Paolo Prandoni, [3]LCAV, EPFL
In this notebook we will build a dual-tone multi-frequency decoder
based on the short-time Fourier transform.
In [1]:
[2]Paolo Prandoni, [3]LCAV, EPFL
In this notebook we will investigate the effect of phase on the
perceptual quality of a sound. It is often said that the human ear is
commercial-grade audio equipment takes place in the magnitude domain
only.
In [1]:
%matplotlib inline
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import IPython
from scipy.io import wavfile
In [2]:
plt.rcParams["figure.fig [2]Paolo Prandoni, [3]LCAV, EPFL
The Karplus-Strong algorithm is a simple method to generate synthetic
sounds with arbitrary pitch. In this notebook we will explore a few
variations of the method to illustrate some basic notions of
discrete-time signal processing.
In [1]:
%matplotlib inline
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import IPython
In [2]:
plt.rcParams["figure.figsize"] [2]Paolo Prandoni, [3]LCAV, EPFL
In this notebook we will explore various ways to implement a system
that changes the voice of a speaker. Typical applications for these
techniques, strictly sorted by plausibility, include international spy
missions and prank telephone calls, and devices such as the one
displayed here can be easily bought on the web... or in a novelty shop.
No description has been provided for t