In previous posts we have explored sampling of continuous-time signals and introduced the Z-transform as a tool to work with discrete-time signals. In this post we address the other end of the process, that is the reconstruction of a signal from its samples.

Continue reading “Sampling. Part III”# Tag: sampling

## Sampling. Part II

In an earlier post we discussed how to obtain the continuous-time Laplace and Fourier transforms of a sampled signal based on the Laplace and Fourier transforms of the original signal. We shall now explore other relationships between those transforms and the Z-transform of the sampled signal.

Continue reading “Sampling. Part II”## Sampling. Part I

Modern control systems are typically implemented in computers that work with periodic samples of signals, that is discrete-time signals, rather than continuous-time signals. A system that produces samples of a given signal is a linear system, albeit a time-varying one. In this post, which starts a series exploring the issue of sampling and discretization, we delve into the nature of a system that can produce such signal samples. More will follow.

Continue reading “Sampling. Part I”## Aliasing and the brain

I am a long-time subscriber of Wired magazine, which I obviously think is a fine publication otherwise I would no longer be a subscriber, but every now and then there will be some “sciency” article that is misleading. The latest one is here.

Continue reading “Aliasing and the brain”