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Related notebooks (15)

Block Processing of Audio Files Using Stateful FIR Filters

Block-processing of audio files[1]¶

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

This notebook shows a simple way to process audio files (in WAV format) in a block-by-block fashion; this is useful in two cases 1. when you want to process a data stream in real time but you can accept a small processing delay; in this case a buffered approach can yield computational gains 2. when you need to process a large file that does not fit entirely into

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

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

Fairness Week 2: COMPAS and Fairness in Machine Learning – Solutions

Fairness Week 2: Predicting recidivism¶{.anchor-link} {#Fairness-Week-2:-Predicting-recidivism}

How to use this notebook Simply read the text and follow the instructions.
This notebook contains code cells, which can be modified and must be executed to see the result of their content.
To execute a cell, select it and click on the play button (▶) in the tool bar, or type Shift + Enter or Ctr + Enter. As the variables contained in a cell are stor

Basic Example of Anderson Localization in a 1D System

Demonstration of Anderson localization[1]¶ This notebook is intended to show a very basic example of the Anderson localization in one-dimensional system. In [1]: import numpy as np from numpy import linalg as LA import matplotlib.pyplot as plt

from future import print_function

from ipywidgets import interact, interactive, fixed, interact_manual import ipywidgets as widgets %matplotlib inline To show the idea of Anderson localization, we can consider 1D chain of

N

atoms with perio

Modeling Epidemics with Signal Processing Techniques

Epidemics and Signal Processing[1]¶

                                      [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

Illustrating Band Structures in Solids: Free Electrons and Atomic Orbitals

In [1]: import numpy as np from numpy import linalg as LA import matplotlib.pyplot as plt

from future import print_function

from ipywidgets import interact, interactive, fixed, interact_manual import ipywidgets as widgets %matplotlib widget The emergence of band structures[1]¶ If you have questions about this notebook, e-mail Oleg Malanyuk (oleg.malanyuk@epfl.ch) This jupyter notebook is intended to provide a illustration of the band structures in solides, starting from the points of v

Investigating the Effect of Phase on Sound Perception

Hearing the phase of a sound[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

Powder X-Ray Diffraction Analysis: Exploring Crystal Structures.

XRay Diffraction[1]¶ The purpose of this notebook is to study the powder XRay diffraction spectra of some systems. When the crystal is hit with an XRay wave, the wave is diffracted only for specific case where the Bragg condition is satisfied for one of the lattice planes in the material. For single crystal diffraction, the condition is satisfied only for specific orientation of the crystal, such that the incident ray has the correct

\theta

value for the plane. In powder XRay data, however, any plane ori

Exploring Frequency Beatings and Intermodulation Effects with Sinusoids

Feel the Beat(s)[1]¶

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

This simple notebook lets you interactively explore the intermodulation effects of two superimposed sinusoids. In [1]:

standard bookkeeping

%matplotlib inline import matplotlib.pyplot as plt import numpy as np from IPython.display import Audio, display

interactivity library:

from ipywidgets import interact, interactive, fixed, interact_manual import ipywidgets as widgets In [2]: plt.rcParams[

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"]

Voice Transformation Techniques Using Digital Signal Processing

A Gallery of Voice Transformers[1]¶

                                      [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

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

Designing FIR Filters Using the Parks-McClellan Algorithm

The Parks-McClellan Filter Design Method[1]¶

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

The Parks-McClellan (PM) algorithm is a clever application of advanced polynomial fitting techniques to the problem of FIR filter design. In this notebook we will explore the key ideas behind the method by considering the design of a simple Type-I lowpass filter. NOTE: This notebook uses interactive widgets. If the interactive controls do not work or show up, please fo

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Related notebooks (15)

Block Processing of Audio Files Using Stateful FIR Filters

Block-processing of audio files[1]¶

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

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

Whistle-Activated Keylock System Implementation

Exploring Quantization and Oversampling through One-Bit Music

Fairness Week 2: COMPAS and Fairness in Machine Learning – Solutions

Fairness Week 2: Predicting recidivism¶{.anchor-link} {#Fairness-Week-2:-Predicting-recidivism}

Basic Example of Anderson Localization in a 1D System

from future import print_function

from ipywidgets import interact, interactive, fixed, interact_manual import ipywidgets as widgets %matplotlib inline To show the idea of Anderson localization, we can consider 1D chain of

N

atoms with perio

Modeling Epidemics with Signal Processing Techniques

Epidemics and Signal Processing[1]¶

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

Illustrating Band Structures in Solids: Free Electrons and Atomic Orbitals

In [1]: import numpy as np from numpy import linalg as LA import matplotlib.pyplot as plt

from future import print_function

Investigating the Effect of Phase on Sound Perception

Hearing the phase of a sound[1]¶

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

Powder X-Ray Diffraction Analysis: Exploring Crystal Structures.

\theta

value for the plane. In powder XRay data, however, any plane ori

Exploring Frequency Beatings and Intermodulation Effects with Sinusoids

Feel the Beat(s)[1]¶

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

This simple notebook lets you interactively explore the intermodulation effects of two superimposed sinusoids. In [1]:

standard bookkeeping

%matplotlib inline import matplotlib.pyplot as plt import numpy as np from IPython.display import Audio, display

interactivity library:

from ipywidgets import interact, interactive, fixed, interact_manual import ipywidgets as widgets In [2]: plt.rcParams[

Exploring the Karplus-Strong Algorithm for Sound Synthesis

The Karplus-Strong Algorithm[1]¶

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

Voice Transformation Techniques Using Digital Signal Processing

A Gallery of Voice Transformers[1]¶

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

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

Designing FIR Filters Using the Parks-McClellan Algorithm

The Parks-McClellan Filter Design Method[1]¶

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