A field guide to equalisation and dynamics processing on rock and electronica records

Popular Music ◽  
2010 ◽  
Vol 29 (2) ◽  
pp. 283-297 ◽  
Author(s):  
Jay Hodgson

AbstractThis paper examines two of the most common signal processing techniques, namely, equalisation and dynamics processing. As with all signal processing techniques, equalisation and dynamics processing modify audio signals in particular ways to suit the evolving requirements of a mix. Rock and electronica records currently feature the most extroverted uses for these techniques and, thus, the clearest examples for a field guide like this. It is for this reason, and this reason alone, that I focus on records from these two genres. I begin this field guide by suggesting a definition for ‘signal processing’ which is sufficiently broad to account for every technique that recordists currently use. I then relate that definition to the concept of ‘frequency response’. In my opinion, this concept is crucial to any understanding of signal processing – a core component of the knowledge base for audio engineering, which is the discipline under which signal processing is typically subsumed; the concept of ‘frequency response’ guides many of the decisions about signal processing that recordists make, especially those concerning equalisation. Finally, I explain how equalisation and dynamics processing work, and I offer a field guide to their most common applications on hit rock and electronica records today.

Author(s):  
Paulo A.A. Esquef ◽  
Luiz W.P. Biscainho

This chapter reviews audio signal processing techniques related to sound generation via additive synthesis. Particular focus will be put on sinusoidal modeling. Each processing stage involved in obtaining a sinusoidal representation for audio signals is described. Then, synthesis techniques that allow reconstructing an audio signal based on a given parametric representation are presented. Finally, some audio applications where sinusoidal modeling is employed are briefly discussed.


Author(s):  
Hector Perez-Meana ◽  
Mariko Nakano-Miyatake

Since the apparition of the first standalone digital signal processor (DSP) in 1980, the development of very-largescale integration (VLSI) technology has allowed an impressive improvement on the performance of signal processing devices. This fact has made it possible to implement more efficient systems for storage, transmission, enhancement, protection, and reproduction of speech and audio signals. Some of these successful applications, shown in Table 1, have contributed to improving the performance of communications, storage, and medical systems, as well as security and copyright protection.


2007 ◽  
Author(s):  
◽  
Stefanus Mare

Detecting and minimising distortion in audio signals is an important aspect of sound engineering. Distortion of a signal passing through an audio system may be caused by a number of factors and it is necessary to detect these effects for optimal sound. The problem is of interest to users and operators of high quality audio equipment and transmission facilities. The objective of this thesis was the development of techniques for the blind identification of distortion in a high quality audio signal using digital signal processing techniques. The techniques developed are based on digital signal processing techniques and statistical analysis of a recorded audio signal, which is treated as a random, non-stationary signal.


2017 ◽  
Author(s):  
Sujeet Patole ◽  
Murat Torlak ◽  
Dan Wang ◽  
Murtaza Ali

Automotive radars, along with other sensors such as lidar, (which stands for “light detection and ranging”), ultrasound, and cameras, form the backbone of self-driving cars and advanced driver assistant systems (ADASs). These technological advancements are enabled by extremely complex systems with a long signal processing path from radars/sensors to the controller. Automotive radar systems are responsible for the detection of objects and obstacles, their position, and speed relative to the vehicle. The development of signal processing techniques along with progress in the millimeter- wave (mm-wave) semiconductor technology plays a key role in automotive radar systems. Various signal processing techniques have been developed to provide better resolution and estimation performance in all measurement dimensions: range, azimuth-elevation angles, and velocity of the targets surrounding the vehicles. This article summarizes various aspects of automotive radar signal processing techniques, including waveform design, possible radar architectures, estimation algorithms, implementation complexity-resolution trade-off, and adaptive processing for complex environments, as well as unique problems associated with automotive radars such as pedestrian detection. We believe that this review article will combine the several contributions scattered in the literature to serve as a primary starting point to new researchers and to give a bird’s-eye view to the existing research community.


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