## Music/Audio Signal Processing

Greetings,

This is my blog from the point of view of a music/audio DSP research engineer / educator. It is informal and largely nontechnical because nearly everything I have to say about signal processing is (or will be) somewhere in my four-book series: Mathematics of DFT with Audio Applications, Introduction to Digital Filters, Physical Audio Signal Processing and

## Time Machine, Anyone?

Abstract: Dispersive 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 :-).

Introduction

## Benford's law solved with DSP

I have a longtime interest in the mystery of 1/f noise. A few years ago I came across Benford’s law, another puzzle that seemed to have many of the same characteristics.

Suppose you collect a large group of seemingly random numbers, such as might appear in a newspaper or financial report. Benford’s law relates to the leading digit of each number, such as "4" in 4.268, "3" in 0.0312, and "9" in -932.34. Since there are nine possible leading digits...

## Waveforms that are their own Fourier Transform

Mea Culpa

There are many scary things about writing a technical book. Can I make the concepts clear? It is worth the effort? Will it sell? But all of these pale compared to the biggest fear: What if I'm just plain wrong? Not being able to help someone is one thing, but leading them astray is far worse.

My book on DSP has now been published for almost ten years. I've found lots of typos, a few misstatements, and many places where the explanations confuse even me. But I have been lucky;...

## Computing Chebyshev Window Sequences

Chebyshev windows (also called Dolph-Chebyshev, or Tchebyschev windows), have several useful properties. Those windows, unlike the fixed Hanning, Hamming, or Blackman window functions, have adjustable sidelobe levels. For a given user-defined sidelobe level and window sequence length, Chebyshev windows yield the most narrow mainlobe compared to any fixed window functions.

However, for some reason, detailed descriptions of how to compute Chebyshev window sequences are not readily available...

## An Interesting Fourier Transform - 1/f Noise

Power law functions are common in science and engineering. A surprising property is that the Fourier transform of a power law is also a power law. But this is only the start- there are many interesting features that soon become apparent. This may even be the key to solving an 80-year mystery in physics.

It starts with the following Fourier transform:

The general form is tα ↔ ω-(α+1), where α is a constant. For example, t2 ↔...

## Components in Audio recognition - Part 1

Audio recognition is defined as the task of recognizing a particular piece of audio (could be music, ring-tone, and speech as well), from a given sample set of audio tracks.

The Human Auditory System (HAS) is unique in that the tasks of "familiarisation" of unknown tracks, and finding "similar" tracks come naturally to us. Tunes from the not-so-recent past can still haunt the human brain many years later, when triggered by a similar tune. The way the brain stores and...

## ES Week Emphasis on Component Based Design

October 7, 2007

Howdy everyone from beautiful Salzburg/Austria,

A week full of presentations on embedded systems at ESWeek was quite a mindful. Similar to most academic conferences, there was only a few papers worth taking back home to think about. Amongst these were:

1. Keynote talk by Hermann Eul from Infineon: He presented Infineon's view on SDR and its evolution. This talk was quite inspirational. However the most interesting slide on complexity of SDR evolution was removed. I wish I could give this...

## Software Defined Radio at SAMOS

Lets start off with so 'hot' SDR track held at SAMOS conference this year. The academic community relatively active in the SDR architecture domain including UMich, WisMad, Linkoping, IMEC and others all presented their views on Software Defined Radio and unveiled a part of their work. We from IMEC 'finally' made our SyncPro architecture public. You can find more about our vector synchronization processor architecture from our

## Compressive Sensing - Recovery of Sparse Signals (Part 1)

November 28, 2015

The amount of data that is generated has been increasing at a substantial rate since the beginning of the digital revolution. The constraints on the sampling and reconstruction of digital signals are derived from the well-known Nyquist-Shannon sampling theorem. To review, the theorem states that a band-limited signal, with the highest frequency of $f_{max}$, can be completely reconstructed from its samples if the sampling rate, $f_{s}$, is at least twice the signal bandwidth. If the...

## Components in Audio recognition - Part 1

Audio recognition is defined as the task of recognizing a particular piece of audio (could be music, ring-tone, and speech as well), from a given sample set of audio tracks.

The Human Auditory System (HAS) is unique in that the tasks of "familiarisation" of unknown tracks, and finding "similar" tracks come naturally to us. Tunes from the not-so-recent past can still haunt the human brain many years later, when triggered by a similar tune. The way the brain stores and...

## GPGPU DSP

January 16, 20101 comment

Greetings dear readers and welcome to my inaugural blog posting!  I'm new to this blogging thing so I hope there is a grace period while I get acclimated.  Before I jump into the meat of this posting allow me to introduce myself and briefly discuss where I intend to go with this blog.Until quite recently I was Director of Software Engineering at a medical device startup, before resigning to strike out on my own.  I have experience in a wide variety of industries, in addition...

July 5, 2011

For the first time, the oral presentations of the International Conference on Accoustics, Speech, and Signal Processing (ICASSP) were recorded and posted online for free. This conference is the best in signal processing and it's diverse as well.

It has a bit speech processing, communication signal processing, and some interesting stuff like bio-inspired signal processing, where Prof. Sayed modeled the behaviour of a group of predetors attacking a herd of preys using distributed least mean...

## Simulink simulation of SSB modulation and demodulation

June 9, 2019

Simulink simulation of SSB modulation and demodulation

blog_ssb_eng.rtfd.zip

## FREE Peer-reviewed IEEE signal processing courses

April 26, 20111 comment

The IEEE signal processing society is offereing FREE peer reviewed courses, though not many, they are peer reviewed and span differenet topics like; wavelets, speech analysis, and statistical detection.

Enjoy

http://cnx.org/lenses/ieeesps/endorsements?b_start:int=0&-C=

## Software Defined Radio at SAMOS

Lets start off with so 'hot' SDR track held at SAMOS conference this year. The academic community relatively active in the SDR architecture domain including UMich, WisMad, Linkoping, IMEC and others all presented their views on Software Defined Radio and unveiled a part of their work. We from IMEC 'finally' made our SyncPro architecture public. You can find more about our vector synchronization processor architecture from our

## ES Week Emphasis on Component Based Design

October 7, 2007

Howdy everyone from beautiful Salzburg/Austria,

A week full of presentations on embedded systems at ESWeek was quite a mindful. Similar to most academic conferences, there was only a few papers worth taking back home to think about. Amongst these were:

1. Keynote talk by Hermann Eul from Infineon: He presented Infineon's view on SDR and its evolution. This talk was quite inspirational. However the most interesting slide on complexity of SDR evolution was removed. I wish I could give this...

## The correct answer to the quiz of @apolin

January 10, 2020

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 mirrored filter

The impulse responses of the filters h1, h2 are complex and the responses to a broadband random signal are also complex. The two spectrum analyzer blocks then show the PSD, typical for analytical...