## Correcting an Important Goertzel Filter Misconception

Correcting an Important Goertzel Filter Misconception

## Complex Down-Conversion Amplitude Loss

●2 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.")

## Specifying the Maximum Amplifier Noise When Driving an ADC

●1 commentI recently learned an interesting rule of thumb regarding the use of an amplifier to drive the input of an analog to digital converter (ADC). The rule of thumb describes how to specify the maximum allowable noise power of the amplifier.

## Towards Efﬁcient and Robust Automatic Speech Recognition: Decoding Techniques and Discriminative Training

Automatic speech recognition has been widely studied and is already being applied in everyday use. Nevertheless, the recognition performance is still a bottleneck in many practical applications of large vocabulary continuous speech recognition. Either the recognition speed is not sufﬁcient, or the errors in the recognition result limit the applications. This thesis studies two aspects of speech recognition, decoding and training of acoustic models, to improve speech recognition performance in different conditions.

## Introduction of C Programming for DSP Applications

●1 commentAppendix C of the book : Real-Time Digital Signal Processing: Implementations, Application and Experiments with the TMS320C55X

## An Introduction To Compressive Sampling

This article surveys the theory of compressive sensing, also known as compressed sensing or CS, a novel sensing/sampling paradigm that goes against the common wisdom in data acquisition.

## Introduction to Compressed Sensing

Chapter 1 of the book: "Compressed Sensing: Theory and Applications".

## Introduction to Real-Time Digital Signal Processing

●2 commentsChapter 1 of the book: Real-Time Digital Signal Processing: Fundamentals, Implementations and Applications, 3rd Edition

## Introduction of C Programming for DSP Applications

●1 commentAppendix C of the book : Real-Time Digital Signal Processing: Implementations, Application and Experiments with the TMS320C55X

## A Pragmatic Introduction to Signal Processing

●4 commentsAn illustrated essay with software available for free download.

## Introduction to Real-Time Digital Signal Processing

●2 commentsChapter 1 of the book: Real-Time Digital Signal Processing: Fundamentals, Implementations and Applications, 3rd Edition

## A Quadrature Signals Tutorial: Complex, But Not Complicated

●3 commentsQuadrature signals are based on the notion of complex numbers and perhaps no other topic causes more heartache for newcomers to DSP than these numbers and their strange terminology of j operator, complex, imaginary, real, and orthogonal. If you're a little unsure of the physical meaning of complex numbers and the j = √-1 operator, don't feel bad because you're in good company. Why even Karl Gauss, one the world's greatest mathematicians, called the j operator the "shadow of shadows". Here we'll shine some light on that shadow so you'll never have to call the Quadrature Signal Psychic Hotline for help. Quadrature signal processing is used in many fields of science and engineering, and quadrature signals are necessary to describe the processing and implementation that takes place in modern digital communications systems. In this tutorial we'll review the fundamentals of complex numbers and get comfortable with how they're used to represent quadrature signals. Next we examine the notion of negative frequency as it relates to quadrature signal algebraic notation, and learn to speak the language of quadrature processing. In addition, we'll use three-dimensional time and frequency-domain plots to give some physical meaning to quadrature signals. This tutorial concludes with a brief look at how a quadrature signal can be generated by means of quadrature-sampling.

## Digital Signal Processor Fundamentals and System Design

●5 commentsDigital Signal Processors (DSPs) have been used in accelerator systems for more than fifteen years and have largely contributed to the evolution towards digital technology of many accelerator systems, such as machine protection, diagnostics and control of beams, power supply and motors. This paper aims at familiarising the reader with DSP fundamentals, namely DSP characteristics and processing development. Several DSP examples are given, in particular on Texas Instruments DSPs, as they are used in the DSP laboratory companion of the lectures this paper is based upon. The typical system design flow is described; common difficulties, problems and choices faced by DSP developers are outlined; and hints are given on the best solution.

## C++ Tutorial

●1 commentThis tutorial is for those people who want to learn programming in C++ and do not necessarily have any previous knowledge of other programming languages. Of course any knowledge of other programming languages or any general computer skill can be useful to better understand this tutorial, although it is not essential. It is also suitable for those who need a little update on the new features the language has acquired from the latest standards. If you are familiar with the C language, you can take the first 3 parts of this tutorial as a review of concepts, since they mainly explain the C part of C++. There are slight differences in the C++ syntax for some C features, so I recommend you its reading anyway. The 4th part describes object-oriented programming. The 5th part mostly describes the new features introduced by ANSI-C++ standard.

## A New Approach to Linear Filtering and Prediction Problems

●1 commentIn 1960, R.E. Kalman published his famous paper describing a recursive solution to the discrete-data linear filtering problem. Since that time, due in large part to advances in digital computing, the Kalman filter has been the subject of extensive research and application, particularly in the area of autonomous or assisted navigation.