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In mathematics, the support of a real-valued function is the subset of the function domain containing the elements which are not mapped to zero. If the domain of is a topological space, then the support of is instead defined as the smallest closed set containing all points not mapped to zero. This concept is used very widely in mathematical analysis. Suppose that is a real-valued function whose domain is an arbitrary set The of written is the set of points in where is non-zero: The support of is the smallest subset of with the property that is zero on the subset's complement. If for all but a finite number of points then is said to have . If the set has an additional structure (for example, a topology), then the support of is defined in an analogous way as the smallest subset of of an appropriate type such that vanishes in an appropriate sense on its complement. The notion of support also extends in a natural way to functions taking values in more general sets than and to other objects, such as measures or distributions. The most common situation occurs when is a topological space (such as the real line or -dimensional Euclidean space) and is a continuous real (or complex)-valued function. In this case, the of , , or the of , is defined topologically as the closure (taken in ) of the subset of where is non-zero that is, Since the intersection of closed sets is closed, is the intersection of all closed sets that contain the set-theoretic support of For example, if is the function defined by then , the support of , or the closed support of , is the closed interval since is non-zero on the open interval and the closure of this set is The notion of closed support is usually applied to continuous functions, but the definition makes sense for arbitrary real or complex-valued functions on a topological space, and some authors do not require that (or ) be continuous. Functions with on a topological space are those whose closed support is a compact subset of If is the real line, or -dimensional Euclidean space, then a function has compact support if and only if it has , since a subset of is compact if and only if it is closed and bounded.
[2]Paolo Prandoni, [3]LCAV, EPFL
In [1]:
import matplotlib.pyplot as plt
import numpy as np
import scipy.signal as sp
import seaborn as sns
sns.set()
In [2]:
plt.rcParams["figure.figsize"] = (14,4)
The basic reproduction number[4]¶
The propagation mechanism of an epidemic such as the one caused by
SARS-CoV-2 virus can be roughly modeled, at least in its inital phase,
as a process in which each infected individ [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
In this notebook we will implement a simple fractional resampler that
uses local Lagrange interpolation. The resampler can be used to perform
any rational sampling rate change (but beware of aliasing when
downsampling!)
In [1]:
import numpy as np
import IPython
from scipy.io import wavfile
Local Lagrange interpolation[4]¶
To perform resampling we will need to compute subsample values and, in [2]Paolo Prandoni, [3]LCAV, EPFL
In this notebook we will use the adaptive LMS filter to estimate the
impulse response of a reverberating room.
A typical use case is handsfree telephony: since the received signal,
amplified and played by the speaker, is picked up by the microphone, we
need to eliminate it from the signal that is transmitted back in order
to avoid a feedback loop. The signal picked up by the microph [2]Paolo Prandoni, [3]LCAV, EPFL
The concept of "basis" for a vector space is one of the most profound
and fruitful ideas in linear algebra. Basis vectors are the "building
blocks" that all other vectors are built from; by "disassembling" a
vector into a linear combination of basis elements we are able to "look
inside" the vector and highlight many of its relevant features.
A vector space has an infinite number o