22.20 Convolution

The convolution of two functions of x, f(x) and g(x), is defined by the definite integral Convolution is defined mathematically but it is possible to understand what it means in pictures. So, if you don’t like mathematics, ignore the next paragraph and the appendices. The definition of convolution can be extended into two, or more… Continue reading 22.20 Convolution

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22.18 Coupled oscillators – Lissajou’s figures

Before you read this, I suggest you read post 18.11 The picture below shows an orthogonal Cartesian coordinate system in which the z-axis is vertical. We are going to think of two pendulums: one oscillates in the xz plane and the other oscillates in the yz plane. For small oscillations, we can consider that the… Continue reading 22.18 Coupled oscillators – Lissajou’s figures

22.17 Model for a simple ecosystem – coupled differential equations

Before you read this, I suggest you read post 19.10. Foxes eat other animals (they are predators), including rabbits: rabbits are eaten by other animals (they are prey), including foxes, but rabbits eat only plants. Now let’s imagine an island that contains foxes and rabbits; there are no other animals for the foxes to eat… Continue reading 22.17 Model for a simple ecosystem – coupled differential equations

22.12 Diffraction, Fourier transforms and image formation

Before you read this, I suggest you read posts 19.20 and 22.11. In post 22.11, we saw that a microscope forms an intermediate image which is then magnified to give a final image. The picture above uses ray-tracing to show how the intermediate image, A’B’, is formed from the object AB. But I now want… Continue reading 22.12 Diffraction, Fourier transforms and image formation