## The DFT Magnitude of a Real-valued Cosine Sequence

●5 commentsThis article may seem a bit trivial to some readers here but, then again, it might be of some value to DSP beginners. It presents a mathematical proof of what is the magnitude of an N-point discrete Fourier transform (DFT) when the DFT's input is a real-valued sinusoidal sequence.

## Sum of Two Equal-Frequency Sinusoids

●4 commentsThe sum of two equal-frequency real sinusoids is itself a single real sinusoid. However, the exact equations for all the various forms of that single equivalent sinusoid are difficult to find in the signal processing literature. Here we provide those equations.

## Using the DFT as a Filter: Correcting a Misconception

●1 commentI have read, in some of the literature of DSP, that when the discrete Fourier transform (DFT) is used as a filter the process of performing a DFT causes an input signal's spectrum to be frequency translated down to zero Hz (DC). I can understand why someone might say that, but I challenge that statement as being incorrect. Here are my thoughts.

## Negative Group Delay

●2 commentsDispersive linear systems with negative group delay have caused much confusion in the past. Some claim that they violate causality, others that they are the cause of superluminal tunneling. Can we really receive messages before they are sent? This article aims at pouring oil in the fire and causing yet more confusion :-).

## Implementing Simultaneous Digital Differentiation, Hilbert Transformation, and Half-Band Filtering

●2 commentsRecently I've been thinking about digital differentiator and Hilbert transformer implementations and I've developed a processing scheme that may be of interest to the readers here on dsprelated.com.

## A New Contender in the Digital Differentiator Race

This blog proposes a novel differentiator worth your consideration. Although simple, the differentiator provides a fairly wide 'frequency range of linear operation' and can be implemented, if need be, without performing numerical multiplications.

## The World's Most Interesting FIR Filter Equation: Why FIR Filters Can Be Linear Phase

●9 commentsThis article discusses a little-known filter characteristic that enables real- and complex-coefficient tapped-delay line FIR filters to exhibit linear phase behavior. That is, this article answers the question: What is the constraint on real- and complex-valued FIR filters that guarantee linear phase behavior in the frequency domain?

## Correcting an Important Goertzel Filter Misconception

Correcting an Important Goertzel Filter Misconception

## Complex Down-Conversion Amplitude Loss

●4 commentsThis article illustrates the signal amplitude loss inherent in a traditional complex down-conversion system. (In the literature of signal processing, complex down-conversion is also called "quadrature demodulation.")

## Peak-to-Average Power Ratio and CCDF

●1 commentPeak to Average Power Ratio (PAPR) is often used to characterize digitally modulated signals. One example application is setting the level of the signal in a digital modulator. Knowing PAPR allows setting the average power to a level that is just low enough to minimize clipping.

## Generating Complex Baseband and Analytic Bandpass Signals

●3 commentsThere are so many different time- and frequency-domain methods for generating complex baseband and analytic bandpass signals that I had trouble keeping those techniques straight in my mind. Thus, for my own benefit, I created a kind of reference table showing those methods. I present that table for your viewing pleasure in this document.

## Implementation of a Tx/Rx OFDM System in a FPGA

●1 commentThe aim of this project consists in the FPGA design and implementation of a transmitter and receiver (Tx/Rx) multicarrier system such the Orthogonal Frequency Division Multiplexing (OFDM). This Tx/Rx OFDM subsystem is capable to deal with with different M-QAM modulations and is implemented in a digital signal processor (DSP-FPGA). The implementation of the Tx/Rx subsystem has been carried out in a FPGA using both System Generator visual programming running over Matlab/Simulink, and the Xilinx ISE program which uses VHDL language. This project is divided into four chapters, each one with a concrete objective. The first chapter is a brief introduction to the digital signal processor used, a field-programmable gate array (FPGA), and to the VHDL programming language. The second chapter is an overview on OFDM, its main advantages and disadvantages in front of previous systems, and a brief description of the different blocks composing the OFDM system. Chapter three provides the implementation details for each of these blocks, and also there is a brief explanation on the theory behind each of the OFDM blocks to provide a better comprehension on its implementation. The fourth chapter is focused, on the one hand, in showing the results of the Matlab/Simulink simulations for the different simulation schemes used and, on the other hand, to show the experimental results obtained using the FPGA to generate the OFDM signal at baseband and then upconverted at the frequency of 3,5 GHz. Finally the conclusions regarding the whole Tx/Rx design and implementation of the OFDM subsystem are given.

## Model Signal Impairments at Complex Baseband

In this article, we develop complex-baseband models for several signal impairments: interfering carrier, multipath, phase noise, and Gaussian noise. To provide concrete examples, we'll apply the impairments to a QAM system. The impairment models are Matlab functions that each use at most seven lines of code. Although our example system is QAM, the models can be used for any complex-baseband signal.

## The Risk In Using Frequency Domain Curves To Evaluate Digital Integrator Performance

This article shows the danger in evaluating the performance of a digital integration network based solely on its frequency response curve. If you plan on implementing a digital integrator in your signal processing work I recommend you continue reading this article.

## The Swiss Army Knife of Digital Networks

●5 commentsThis article describes a general discrete-signal network that appears, in various forms, inside so many DSP applications.

## A Wide-Notch Comb Filter

●1 commentThis article describes a linear-phase comb filter having wider stopband notches than a traditional comb filter.

## Reduced-Delay IIR Filters

●2 commentsThis document describes a straightforward method to significantly reduce the number of necessary multiplies per input sample of traditional IIR lowpass and highpass digital filters.

## A Review of Physical and Perceptual Feature Extraction Techniques for Speech, Music and Environmental Sounds

●3 commentsEndowing machines with sensing capabilities similar to those of humans is a prevalent quest in engineering and computer science. In the pursuit of making computers sense their surroundings, a huge effort has been conducted to allow machines and computers to acquire, process, analyze and understand their environment in a human-like way. Focusing on the sense of hearing, the ability of computers to sense their acoustic environment as humans do goes by the name of machine hearing. To achieve this ambitious aim, the representation of the audio signal is of paramount importance. In this paper, we present an up-to-date review of the most relevant audio feature extraction techniques developed to analyze the most usual audio signals: speech, music and environmental sounds. Besides revisiting classic approaches for completeness, we include the latest advances in the field based on new domains of analysis together with novel bio-inspired proposals. These approaches are described following a taxonomy that organizes them according to their physical or perceptual basis, being subsequently divided depending on the domain of computation (time, frequency, wavelet, image-based, cepstral, or other domains). The description of the approaches is accompanied with recent examples of their application to machine hearing related problems.

## The DFT Magnitude of a Real-valued Cosine Sequence

●5 commentsThis article may seem a bit trivial to some readers here but, then again, it might be of some value to DSP beginners. It presents a mathematical proof of what is the magnitude of an N-point discrete Fourier transform (DFT) when the DFT's input is a real-valued sinusoidal sequence.