An atom and the solar system

Sampling and the Mysterious Scaling Factor

This post treats the signals in continuous time which is different than the approach I adopted in my book. The book deals exclusively in discrete time. Some time ago, I came across an interesting problem. In the explanation of sampling process, a representation of impulse sampling shown in Figure below is illustrated in almost every textbook on DSP and communications. The question is: how is it possible that during sampling, the frequency axis gets scaled by $1/Ts$ — a very large number? For an ADC operating at 10 MHz for example, the amplitude of the desired spectrum and spectral replicas

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DTMF spectrum for key 6

Goertzel Algorithm – Evaluating DFT without DFT

The Discrete Fourier Transform (DFT) computes the contribution of $N$ sinusoids that come together to form any input signal. However, in some applications, we are only interested in contributions from one or a few sinusoids. This is where the Goertzel algorithm, proposed by Gerald Goertzel in 1958, steps in. The Goertzel algorithm evaluates the individual terms of the DFT in an efficient manner. We explain its derivation and implementation with the help of DTMF signals. DTMF Signal Generation In the early days of telephone, you could not call anyone directly. Instead, a telephone operator used to sit on the other

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Width of a sinc signal increases and approaches a constant, just like an eagle spreading its wings

A Unit Impulse in Continuous-Time

This post treats the signals in continuous time which is different than the approach I adopted in my book which deals exclusively in discrete time. A unit impulse is defined as \begin{equation*} \delta (t) = \displaystyle{\lim_{\Delta \to 0}} \begin{cases} \frac{1}{\Delta} & -\frac{\Delta}{2} < t < +\frac{\Delta}{2} \\ 0 & \text{elsewhere} \end{cases} \end{equation*} The result is an impulse with zero width and infinite height, but a consequence of defining it in this way is that the area under the curve is unity. \begin{equation*} \text{Area under a rectangle} = \Delta \cdot \frac{1}{\Delta} = 1 \end{equation*} This is shown in Figure below. Stated

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A matched filter in continuous frequency domain along with the corresponding frequency matched filter for excess bandwidth 0.25

Band Edge Filters for Carrier and Timing Synchronization

Band edge filters for carrier frequency and symbol timing synchronization is a very interesting topic that elegantly relates the tool (DSP) to the application (SDR design). This article is a short summary of where they originate from and what role they play for synchronization purpose. A Carrier Frequency Offset (CFO) arises due to a mismatch between Tx and Rx local oscillators as well as a phenomenon known as Doppler effect. In some other articles on this website, you will also find information on the Phase Locked Loop (PLL) in the context of carrier phase and timing synchronization. There is another

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Time and frequency response of a lowpass FIR filter designed with Parks-McClellan algorithm for N=33

Finite Impulse Response (FIR) Filters

We learned in the concept of frequency that most signals of practical interest can be considered as a sum of complex sinusoids oscillating at different frequencies. The amplitudes and phases of these sinusoids shape the frequency contents of that signal and are drawn through magnitude response and phase response, respectively. In DSP, a regular goal is to modify these frequency contents of an input signal to obtain a desired representation at the output. This operation is called filtering and it is the most fundamental function in the whole field of DSP. It is possible to design a system, or filter,

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