Concept

Sequence space

Related notebooks (8)

The plotted function is the superimposition of $n$ 2d-sine functions centered in $(0,Y_i)$: $$f(x,y)=\sin\big(p\cdot\sqrt{x^2+(y-Y_i)^2}\big)$$ The parameters that can be changed are: -- $n$ the number of sources (start with 2) -- $d$ the distance between sources -- $p$ the periodicity. Higher periodicity means shorter wavelength. $p =2\pi / \lambda$. Note that in electron microscopy the usual convention is to define the wave vector as $k=1/\lambda$. -- $f$ the field o

Understanding the Haar Basis for Grayscale Image Compression

A Basis for Grayscale Images[1]¶

                                      [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

Exploring the Karplus-Strong Algorithm for Sound Synthesis

The Karplus-Strong Algorithm[1]¶

                                      [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"]

Adaptive Echo Cancellation using LMS Filter

Adaptive Echo Cancellation[1]¶

                                      [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

Whistle-Activated Keylock System Implementation

Whistling Keylock[1]¶ In this notebook we will implement a simple "whistle-activated" keylock, that is, an access control system where the password is a pre-defined melody. To program the lock, you record your musical passphrase and then, to open the lock, you whistle it back. Although the implementation will be simple and skip most of the fine details that would be necessary to produce a truly robust system, we need to take into account at least the following points: * The syste

Exploring Quantization and Oversampling through One-Bit Music

One-Bit Music[1]¶ In this notebook we will talk about quantization and oversampling and we will do so by taking a trip down memory lane to revisit the early from monophonic square waves, introduce polyphony by way of pulse-width modulation and finish with the basics of sigma-delta quantization. pacman In [1]: import matplotlib import matplotlib.pyplot as plt import numpy as np import scipy.signal as sp from scipy.io import wavfile import IPython In [2]: import sys ! wget -q -O mus

Understanding and Plotting the Discrete Fourier Transform (DFT)

Plotting the DFT[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

In this notebook we will look at the practical issues associated to plotting the DFT and in particular the DFT of real-world signals. We will examine how to map the DFT coefficients to real-world frequencies and we will investigate the frequency resolution of the DFT and the effects of zero padding. In [1]:

first our usual bookkeeping

%matplotlib inline import matplotlib import matplotlib.p

Building a Dual-Tone Multi-Frequency (DTMF) Decoder using Short-Time Fourier Transform

Dual-tone multi-frequency (DTMF) signaling[1]¶

                                      [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]:

first our usual bookkeeping

%matplotlib inline import matplotlib import matplotlib.pyplot as plt import numpy as np import IPython In [2]: plt.rcParams["figure.figsize"] = (14,4)

Introduction[4]¶ DTMF signaling is the way analog phones send the n

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Related notebooks (8)

Wave Interference

Understanding the Haar Basis for Grayscale Image Compression

A Basis for Grayscale Images[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

Exploring the Karplus-Strong Algorithm for Sound Synthesis

The Karplus-Strong Algorithm[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

Adaptive Echo Cancellation using LMS Filter

Adaptive Echo Cancellation[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

Whistle-Activated Keylock System Implementation

Exploring Quantization and Oversampling through One-Bit Music

Understanding and Plotting the Discrete Fourier Transform (DFT)

Plotting the DFT[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

first our usual bookkeeping

%matplotlib inline import matplotlib import matplotlib.p

Building a Dual-Tone Multi-Frequency (DTMF) Decoder using Short-Time Fourier Transform

Dual-tone multi-frequency (DTMF) signaling[1]¶

                                      [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]:

first our usual bookkeeping

%matplotlib inline import matplotlib import matplotlib.pyplot as plt import numpy as np import IPython In [2]: plt.rcParams["figure.figsize"] = (14,4)

Introduction[4]¶ DTMF signaling is the way analog phones send the n