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Positive psychology is a branch of psychology that studies the conditions that contribute to the optimal functioning of people, groups, and institutions. It studies "positive subjective experience, positive individual traits, and positive institutions... it aims to improve quality of life." It is a field of study that has grown as individuals and researchers look for common ground on better well-being. Positive psychology began as a new domain of psychology in 1998 when Martin Seligman chose it as the theme for his term as president of the American Psychological Association. It is a reaction against past practices, which tended to focus on mental illness and emphasized maladaptive behavior and negative thinking. It builds on the humanistic movement by Abraham Maslow, Rollo May, James Martin, and Carl Rogers, which encourages an emphasis on happiness, well-being, and positivity. Positive psychology largely relies on concepts from the Western philosophical tradition, such as the Aristotelian concept of eudaimonia, which is typically rendered in English with the terms "flourishing", "the good life" or even "happiness". Positive psychologists study empirically the conditions and processes that contribute to flourishing, subjective well-being and happiness - often using these terms interchangeably. Positive psychologists suggested a number of factors may contribute to happiness and subjective well-being, for example: social ties with a spouse, family, friends, colleagues, and wider networks; membership in clubs or social organizations; physical exercise; and the practice of meditation. Spirituality can also lead to increased individual happiness and well-being. Spiritual practice and religious commitment is a possible source for increased well-being studied within positive psychology. Happiness may rise with increasing income, though it may plateau or even fall when no further gains are made or after a certain cut-off amount.
[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 [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 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]:
[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