Using noise to characterize linear systems

 — 

In two previous posts, I talked about linear systems and how we can easily characterize them by stimulating with specific classes of functions, such as impulses or sine functions. Here, I would like to talk about a third way of characterizing linear systems, that is commonly used: Responses to noise …

Category: Theory Tags:

Linear systems in the Fourier domain

 — 

In a previous blog post, we discussed how linear systems can be characterized by their impulse response. However, it is often difficult to stimulate a linear system with perfect pulses. An alternative—and often insightful—way of characterizing a linear system is through its frequency response.

Characterization of linear systems …

Category: Theory Tags:

Basic linear systems analysis

 — 

In psychophysics, we attempt to characterize the visual system by means of input-output relations. We present an image to the observer (input) and we study how the observer's response (output) changes as we change properties of the image. Linear systems are about the simplest input-output systems and although they are …

Category: Theory Tags:

Monte carlo methods in python

 — 

Monte carlo methods are a class of statistical procedures that rely on random number generation to arrive at conclusions. There are many, arbitrarily complex methods that can involve pretty elaborate simulation strategies. This post will focus on two pretty simple, non-parametric methods and how to implement them in python. These …

Category: Statistics Tags:

Understanding gamma calibration

 — 

When we look at an image on a computer monitor, it seems that what we see is actually what is stored in the image. This is not quite true. Most modern monitors apply a number of additional transformations to the image "improve" its appearance — higher contrast, brighter colors, ... Although this …

Category: Stimuli and displays Tags:

© Ingo Fruend 2016

Powered by Pelican