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Second Order Discrete-Time System Demonstration

Neil Robertson

Discrete-time systems are remarkable: the time response can be computed from mere difference equations, and the coefficients ai, bi of these equations are also the coefficients of H(z). Here, I try to illustrate this remarkableness by converting a continuous-time second-order system to an approximately equivalent discrete-time system. With a discrete-time model, we can then easily compute the time response to any input. But note that the goal here is as much to understand the discrete-time model as it is to find the response.

A Beginner's Guide To Cascaded Integrator-Comb (CIC) Filters

Rick Lyons

This article discusses the behavior, mathematics, and implementation of cascaded integrator-comb filters.

The correct answer to the quiz of @apolin

Josef Hoffmann

The correct answer to the @apolin quiz can be easily explained using the following Simulink model: In MATLAB you have to initialize the two filters: h = dftmtx (8); h1 = h (3, :); % The filter of the quiz h2 = h (7, :); % The...

A Free DSP Laboratory

Stephen Morris

Getting Started In Audio DSPImagine you're starting out studying DSP and your particular interest is audio. Wouldn't it be nice to have access to some audio signals and the tools to analyze and modify them? In the old days, a laboratory like this...

Polynomial calculations on an FIR filter engine, part 1

Kendall Castor-Perry

Polynomial evaluation is structurally akin to FIR filtering and fits dedicated filtering engines quite well, with certain caveats. It’s a technique that has wide applicability. This two-part note discusses transducer and amplifier non-linearity...

Plotting Discrete-Time Signals

Neil Robertson

A discrete-time sinusoid can have frequency up to just shy of half the sample frequency. But if you try to plot the sinusoid, the result is not always recognizable. For example, if you plot a 9 Hz sinusoid sampled at 100 Hz, you get the result shown in the top of Figure 1, which looks like a sine. But if you plot a 35 Hz sinusoid sampled at 100 Hz, you get the bottom graph, which does not look like a sine when you connect the dots. We typically want the plot of a sampled sinusoid to resemble its continuous-time version. To achieve this, we need to interpolate.

5G NR QC-LDPC Encoding Algorithm

Lyons Zhang

3GPP 5G has been focused on structured LDPC codes known as quasi-cyclic low-density parity-check (QC-LDPC) codes, which exhibit advantages over other types of LDPC codes with respect to the hardware implementations of encoding and decoding using...

Interpolation Basics

Neil Robertson

This article covers interpolation basics, and provides a numerical example of interpolation of a time signal. Figure 1 illustrates what we mean by interpolation. The top plot shows a continuous time signal, and the middle plot shows a sampled version with sample time Ts. The goal of interpolation is to increase the sample rate such that the new (interpolated) sample values are close to the values of the continuous signal at the sample times [1]. For example, if we increase the sample rate by the integer factor of four, the interpolated signal is as shown in the bottom plot. The time between samples has been decreased from Ts to Ts/4.

Round-robin or RTOS for my embedded system

Manuel Herrera

First of all, I would like to introduce myself. I am Manuel Herrera. I am starting to write blogs about the situations that I have faced over the years of my career and discussed with colleagues.To begin, I would like to open a conversation...

Somewhat Off Topic: Deciphering Transistor Terminology

Rick Lyons

I recently learned something mildly interesting about transistors, so I thought I'd share my new knowledge with you folks. Figure 1 shows a p-n-p transistor comprising a small block of n-type semiconductor sandwiched between two blocks of p-type...