Underwater acoustic signal analysis: preprocessing and classification by deep learning
نویسندگان
چکیده
منابع مشابه
Association Rules Enhanced Classification of Underwater Acoustic Signal
Classification of underwater acoustic signal is one of the important fields of pattern recognition. Inspired by the experience of training man experts in sonar, we propose a two-phase training algorithm to exploit the association rules to reveal the understandable intrinsic rules contributing to correct classification in the known misclassification datasets in this paper. Preliminary experiment...
متن کاملUnderwater Acoustic Signal Processing Workshop
Listings Underwater Acoustic Communications: Working at the Intersection of Physics, Signal Processing, and Communications Theory James C. Preisig Woods Hole Oceanographic Institution WHIO, MS #11 Woods Hole, MA 02543 [email protected] The underwater environment is widely regarded as one of the most difficult communication channels. Underwater acoustic communications systems are challenged by t...
متن کاملRobust Classification Techniques for Acoustic Signal Analysis
Classiication of short duration acoustic signals can be very diicult due to the high degree of variability in the signatures. Input feature vectors, resulting from wavelets or short time Fourier analysis, are typically of high dimensionality, noisy, and contain incomplete information. In this paper, robust artiicial neu-ral networks (ANNs) are identiied that are less sensitive to noisy feature ...
متن کاملCharacteristics Analysis of HFM Signal over Underwater Acoustic Channels
Abstract For pulse compression characteristics and not easily affected by noise, linear frequency modulation signal are widely used in underwater acoustic communication. This paper analyzes the characteristics of hyperbolic frequency modulation signal over underwater acoustic channels. Compared with linear frequency modulation signal, hyperbolic frequency modulation has the same performance of ...
متن کاملBat detective—Deep learning tools for bat acoustic signal detection
Passive acoustic sensing has emerged as a powerful tool for quantifying anthropogenic impacts on biodiversity, especially for echolocating bat species. To better assess bat population trends there is a critical need for accurate, reliable, and open source tools that allow the detection and classification of bat calls in large collections of audio recordings. The majority of existing tools are c...
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: Neural Network World
سال: 2020
ISSN: 2336-4335
DOI: 10.14311/nnw.2020.30.007