Real-time localization and tracking of musical instruments with spherical microphone arrays

2017 ◽  
Vol 141 (5) ◽  
pp. 3726-3726
Author(s):  
Jonathan Mathews ◽  
Jonas Braasch
Keyword(s):  
Real Time ◽  
Musical Instruments ◽  
Microphone Arrays ◽  
Spherical Microphone Arrays ◽  
Localization And Tracking

The Analysis of Electroacoustic Music: from sources to invariants

2006 ◽  
Vol 11 (2) ◽  
pp. 101-112 ◽  
Author(s):  
BRUNO BOSSIS
Keyword(s):  
Real Time ◽  
Electroacoustic Music ◽  
Musical Instruments ◽  
Documentary Sources ◽  
Synthetic Vision ◽  
Technological Context ◽  
Systematic Musicology ◽  
Many Sources ◽  
Musical Genres

The musicologist is confronted with many situations during the analysis of electroacoustic music, whether on support media, mixed, or real-time. Musical genres and styles vary greatly, and the collection of electronic musical instruments has also proven to be very heterogeneous. The intrinsic characteristics of the electroacoustic parts and their scoring create serious limitations. Furthermore, many sources remain inaccessible or are already lost. Thus the preoccupation with documentary sources related to the acts of creation, interpretation, and technological context becomes more and more pressing. It is now essential to formulate a synthetic vision of this music, which has existed for half a century, and to pursue the search for invariants. This work must be based on a rigorous methodology that has yet to be developed. More generally speaking, the goal is to establish the terms and conditions of a systematic musicology of electroacoustics.

An Efficient Smartphone Assisted Indoor Localization with Tracking Approach using Glowworm Swarm Optimization Algorithm

2021 ◽  
pp. 101-107
Author(s):  
Mohammad Alshehri ◽  
Keyword(s):  
Real Time ◽  
Indoor Localization ◽  
Initial Position ◽  
Swarm Optimization ◽  
The Real ◽  
Assisted Navigation ◽  
Glowworm Swarm Optimization ◽  
Tracking Process ◽  
Wide Range ◽  
Localization And Tracking

Presently, a precise localization and tracking process becomes significant to enable smartphone-assisted navigation to maximize accuracy in the real-time environment. Fingerprint-based localization is the commonly available model for accomplishing effective outcomes. With this motivation, this study focuses on designing efficient smartphone-assisted indoor localization and tracking models using the glowworm swarm optimization (ILT-GSO) algorithm. The ILT-GSO algorithm involves creating a GSO algorithm based on the light-emissive characteristics of glowworms to determine the location. In addition, the Kalman filter is applied to mitigate the estimation process and update the initial position of the glowworms. A wide range of experiments was carried out, and the results are investigated in terms of distinct evaluation metrics. The simulation outcome demonstrated considerable enhancement in the real-time environment and reduced the computational complexity. The ILT-GSO algorithm has resulted in an increased localization performance with minimal error over the recent techniques.

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