Results 11 to 20 of about 70,555 (280)
Radio Frequency Interference Detection and Mitigation Algorithms Based on Spectrogram Analysis
Algorithms, 2011 Radio Frequency Interference (RFI) detection and mitigation algorithms based on a signal’s spectrogram (frequency and time domain representation) are presented.
Adriano Camps
exaly +3 more sources
Elektronika ir Elektrotechnika, 2022 Three main approaches on how audio signals can be used as input to a deep learning model are: extracting hand-crafted features from audio signals, mapping audio signals into appropriate images such as spectrogram-like ones, and using directly raw audio ...
Dejan G. Ciric +3 more
doaj +1 more source
Spectrogram Analysis of Genomes [PDF]
EURASIP Journal on Advances in Signal Processing, 2004 We performed frequency-domain analysis in the genomes of various organisms using tricolor spectrograms, identifying several types of distinct visual patterns characterizing specific DNA regions. We relate patterns and their frequency characteristics to the sequence characteristics of the DNA.
David Sussillo +2 more
openaire +3 more sources
Deep learning bird song recognition based on MFF-ScSEnet
Ecological Indicators, 2023 Bird diversity plays an important role in ecological balance, and bird song identification is of great practical significance. The spectrum generated by feature extraction shows good performance on classification.
Shipeng Hu +5 more
doaj +1 more source
EURASIP Journal on Advances in Signal Processing, 2010 A novel method, called adaptive pulse coupled neural network (AD-PCNN) using a two-stage denoising strategy, is proposed to reduce noise and speckle in the spectrograms of Doppler blood flow signals.
Haiyan Li, Yufeng Zhang, Dan Xu
doaj +2 more sources
Spectrograms Are Sequences of Patches
CoRR, 2022 Self-supervised pre-training models have been used successfully in several machine learning domains. However, only a tiny amount of work is related to music. In our work, we treat a spectrogram of music as a series of patches and design a self-supervised model that captures the features of these sequential patches: Patchifier, which makes good use of ...
Leyi Zhao, Yi Li
openaire +2 more sources
Multibeam Doppler Sensor-Based Non-Contact Heartbeat Detection Using Beam Diversity
IEEE Access, 2022 Heartbeat detection could enable various applications in the medical and health care fields. In particular, non-contact heartbeat detection can be acceptable for those who have difficulty wearing devices, such as burn patients and infants.
Tsukiko Kitagawa +3 more
doaj +1 more source
Nonlinear time-warping made simple: a step-by-step tutorial on underwater acoustic modal separation with a single hydrophone [PDF]
, 2020 © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Bonnel, J., Thode, A., Wright, D., & Chapman, R.
Bonnel, Julien +3 more
core +1 more source
, 2005 Speech and other natural sounds show high temporal correlation and smooth spectral evolution punctuated by a few, irregular and abrupt changes. In a conventional Hidden Markov Model (HMM), such structure is represented weakly and indirectly through transitions between explicit states representing 'steps' along such smooth changes.
Reyes-Gomez, Manuel +2 more
openaire +2 more sources
A Deep Neural Network Model for Speaker Identification
Applied Sciences, 2021 Speaker identification is a classification task which aims to identify a subject from a given time-series sequential data. Since the speech signal is a continuous one-dimensional time series, most of the current research methods are based on ...
Feng Ye, Jun Yang
doaj +1 more source