Sound Source Localization with CS Based Compressed Neural Network
نویسندگان
چکیده
منابع مشابه
A Neural Network for Sound Source Separation
The brain possesses the remarkable capability to filter incoming signals of multiple speakers in such a way that the subject’s attention can be focused on a single sound source, the other sources being suppressed. Much effort has been spent in order to mimic this behaviour by machines or clever algorithms which try to reconstruct the separated sources. A key issue in such attempts is the questi...
متن کاملBiomimetic Sound-Source Localization
Sound-source localization systems typically comprise free-field microphone arrays. In nature, directional acoustic sensing evolved to rely on diffraction about the head with only two ears. For localization, the brain uses the resultant frequency-dependent acoustic phase and intensity differences between the two ears. We conceive a biomimetic artificial head with microphones placed on its surfac...
متن کاملSimilarity-based Sound Source Localization with a Coincident Microphone Array
This paper presents a robust, accurate sound source localization method using a compact, near-coincident microphone array. We derive features by combining the microphone signals and determine the direction of a single sound source by similarity matching. Therefore, the observed features are compared with a set of previously measured reference features, which are stored in a look-up table. By pr...
متن کاملSound Source Localization with Non-calibrated Microphones
We propose a new method for localizing a sound source in a known space with non-calibrated microphones. Our method does not need the accurate positions of the microphones that are required by traditional sound source localization. Our method can make use of wide variety of microphone layout in a large space because it does not need calibration step on installing microphones. After a number of s...
متن کاملSound Source Localization through 8 MEMS Microphones Array Using a Sand-Scorpion-Inspired Spiking Neural Network
Sand-scorpions and many other arachnids perceive their environment by using their feet to sense ground waves. They are able to determine amplitudes the size of an atom and locate the acoustic stimuli with an accuracy of within 13° based on their neuronal anatomy. We present here a prototype sound source localization system, inspired from this impressive performance. The system presented utilize...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: American Journal of Signal Processing
سال: 2012
ISSN: 2165-9354
DOI: 10.5923/j.ajsp.20110101.01