Concept

Number theory

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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

Simulating Electron Motion in 2D Materials Using the Drude Model - Basic

Drude model considers electrons small solid particles traveling through lattices as a stationary array of heavier and bigger atoms. The model use "mean free time" as a measure of the frequency an electron gets scattered. This jupyter notebook makes use of this concept and uses stochastic method to simulat electrons traveling through a 2D material of finite width but infinite length."

"#### First we setup the simulation parameters such as the external electric field, number of electrons (default

Estimation of Electron Density and Mean Free Time for Transparent Conductors

Chapter 1: Transparent Conductors[1]¶ Instruction: The purpose of this notebook is to try and find values of electron density and mean free time for a material suitable to be used as a transparent conductors. The final estimate should be the order of the two parameters to be used[2]¶ In [1]: import numpy as np from bokeh.io import push_notebook, output_notebook, show from bokeh.layouts import row, column from bokeh.plotting import figure output_notebook() from ipywidgets import interact from collect

Simulating Electron Motion in 2D Materials Using the Drude Model - Advanced

Drude model considers electrons small solid particles traveling through lattices as a stationary array of heavier and bigger atoms. The model use "mean free time" as a measure of the frequency an electron gets scattered. This jupyter notebook makes use of this concept and uses stochastic method to simulate electrons traveling through a 2D material of finite width but infinite length."

First we setup the simulation parameters such as the external electric field, number of electrons (default to 1)

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

Implementing a Fractional Resampler using Local Lagrange Interpolation

FIR Resampling[1]¶

                                      [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

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

Numerical Precision in DFT Computation

Numerical Precision in DFT Computation[1]¶

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

In [1]:

first our usual bookkeeping

%matplotlib inline import matplotlib import matplotlib.pyplot as plt import numpy as np In this notebook we will look at some numerical issues associated to the DFT; in particular we we will look at the differences in precision between the "naive" way of computing the DFT and the FFT algorithm. As a quick reminder, the definitions of t

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

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

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

Introduction to Reciprocal Lattices with Periodic Boundary Conditions.

Real vs. Reciprocal Space in 2D[1]¶ Introduction[2]¶ In this short notebook, we will introduce the lattice with periodic(Born- von Karman) boundary condition. Following the boundary condition, there is a transformation from real lattice to the reciprocal lattice. In the code below, we define a1 and a2 through cartesian vectors. Hence, the reciprocal vectors will be the original rotated by 90 degrees multiplied by 2pi and divided by the area of the unit cell (|a1xa2|) In [1]: i

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

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"]

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

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

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 Hund s Rules

numbers

S

L

and

J

of an isolated atom or ion from its electronic configuration. Considering a partially filled electronic shell, the following three rules have to be applied in the order given below: 1. The total spin angular momentum

S=\Sigma|m_s|

takes its maximum possible value; 2. The total orbital angular momentum

L=\Sigma|m_l|

is maximized; 3. For more than half-filled shell, the total angular momentum number

J=L+S

, otherwise

J=\vert L-S \vert

. The sl

Advantages of Digital Transmission over Analog Transmission

[1]Paolo Prandoni, [2]EPFL Analog vs Digital Transmission In this notebook we will explore the advantages of digital transmission over analog transmission. We will model the case of transmission over a long (e.g. transoceanic) cable in which several repeaters are used to compensate for the attenuation incurred by the signal. In [1]: import matplotlib import matplotlib.pyplot as plt import numpy as np import IPython from scipy.io import wavfile plt.rcParams["figure.figsize"] = (14,4)

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[

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Wave Interference

Simulating Electron Motion in 2D Materials Using the Drude Model - Basic

Drude model considers electrons small solid particles traveling through lattices as a stationary array of heavier and bigger atoms. The model use "mean free time" as a measure of the frequency an electron gets scattered. This jupyter notebook makes use of this concept and uses stochastic method to simulat electrons traveling through a 2D material of finite width but infinite length."

"#### First we setup the simulation parameters such as the external electric field, number of electrons (default

Estimation of Electron Density and Mean Free Time for Transparent Conductors

Simulating Electron Motion in 2D Materials Using the Drude Model - Advanced

Drude model considers electrons small solid particles traveling through lattices as a stationary array of heavier and bigger atoms. The model use "mean free time" as a measure of the frequency an electron gets scattered. This jupyter notebook makes use of this concept and uses stochastic method to simulate electrons traveling through a 2D material of finite width but infinite length."

First we setup the simulation parameters such as the external electric field, number of electrons (default to 1)

Adaptive Echo Cancellation using LMS Filter

Adaptive Echo Cancellation[1]¶

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

Implementing a Fractional Resampler using Local Lagrange Interpolation

FIR Resampling[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

Numerical Precision in DFT Computation

Numerical Precision in DFT Computation[1]¶

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

In [1]:

first our usual bookkeeping

Modeling Epidemics with Signal Processing Techniques

Epidemics and Signal Processing[1]¶

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

Understanding the Haar Basis for Grayscale Image Compression

A Basis for Grayscale Images[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

Introduction to Reciprocal Lattices with Periodic Boundary Conditions.

Designing FIR Filters Using the Parks-McClellan Algorithm

The Parks-McClellan Filter Design Method[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

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

Voice Transformation Techniques Using Digital Signal Processing

A Gallery of Voice Transformers[1]¶

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

Exploring Quantization and Oversampling through One-Bit Music

Understanding Hund s Rules

numbers

S

L

and

J

S=\Sigma|m_s|

takes its maximum possible value; 2. The total orbital angular momentum

L=\Sigma|m_l|

is maximized; 3. For more than half-filled shell, the total angular momentum number

J=L+S

, otherwise

J=\vert L-S \vert

. The sl

Advantages of Digital Transmission over Analog Transmission

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[