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Showing 1 to 20 of 21 for “"signal separation"”.

  1. Co-channel digital signal separation : application and practice

    … the theory and application of co-channel digital signal separation techniques. We set up a test-bed with the GNU Software Defined Radio (SDR) platform where we implement and experiment with single-antenna signal separation algorithms. We mainly investigate linearly-modulated digital signals. To do …

    mit Repository record for Co-channel digital signal separation : application and practice (opens in a new tab)

  2. Constrained Clustering for Frequency Hopping Spread Spectrum Signal Separation

    Frequency Hopping Spread Spectrum (FHSS) signaling is used across many devices operating in both regulated and unregulated bands. In either situation, if there is a malicious device operating within these bands, or more simply a user operating out of the required specifications, the identification …

    vt Repository record for Constrained Clustering for Frequency Hopping Spread Spectrum Signal Separation (opens in a new tab)

  3. Signal separation of musical instruments: simulation-based methods for musical signal decomposition and transcription

    … presents techniques for the modelling of musical signals, with particular regard to monophonic and polyphonic pitch estimation. Musical signals are modelled as a set of notes, each comprising of a set of harmonically-related sinusoids. An hierarchical model is presented that is very general and …

    cambridge Repository record for Signal separation of musical instruments: simulation-based methods for musical signal decomposition and transcription (opens in a new tab)

  4. Machine Learning for Data-Driven Signal Separation and Interference Mitigation in Radio-Frequency Communication Systems

    Single-channel source separation for radio-frequency (RF) systems is a challenging problem relevant to key applications, including wireless communications, radar, and spectrum monitoring. This thesis addresses the challenge by focusing on data-driven approaches for source separation, leveraging …

    mit Repository record for Machine Learning for Data-Driven Signal Separation and Interference Mitigation in Radio-Frequency Communication Systems (opens in a new tab)

  5. On the Use of Uncalibrated Digital Phased Arrays for Blind Signal Separation for Interference Removal in Congested Spectral Bands

    … to take advantage of spatially-separated signal sources is apparent. Traditional phased array beamforming techniques used for interference removal rely on perfect calibration between elements and precise knowledge of the array configuration; however, if the exact array configuration is not …

    vt Repository record for On the Use of Uncalibrated Digital Phased Arrays for Blind Signal Separation for Interference Removal in Congested Spectral Bands (opens in a new tab)

  6. Seismic ground-roll separation using sparsity promoting L1 minimization

    … as a sparsifying basis in which to perform signal separation techniques that can preserve reflector information while increasing ground roll removal. We examine two signal separation techniques, a block-coordinate relaxation method and a Bayesian separation method. The derivations and …

    ubc Repository record for Seismic ground-roll separation using sparsity promoting L1 minimization (opens in a new tab)

  7. Signal reconstruction from discrete-time Wigner distribution

    … for time-frequency analysis of rumvstationary signals. Wigner distribution is a bilinear signal transformation which provides two dimensional time-frequency characterization of one dimensional signals. Although much work has been done recently in signal analysis and applications using Wigner …

    vt Repository record for Signal reconstruction from discrete-time Wigner distribution (opens in a new tab)

  8. Extraction of Blood Volume Pulse Morphology from Facial Videos Using an LSTM-Based Temporal Encoder-Decoder Model

    … a method for extracting blood volume pulse (BVP) signals from facial videos, moving beyond basic heart rate estimation to capture full pulse waveforms. Our approach adapts techniques from audio signal separation and applies them to video, using a machine learning model capable of processing …

    vt Repository record for Extraction of Blood Volume Pulse Morphology from Facial Videos Using an LSTM-Based Temporal Encoder-Decoder Model (opens in a new tab)

  9. Accurate noninvasive monitoring of fetal tissue oxygenation level

    … is the first to achieve accurate, multichannel signal separation from two distinct layers. We conducted Monte Carlo simulations and experiments on a fiber-based ToF-NIRS prototype. Our prototype system achieves <3% estimation error in a two-layer tissue phantom. Additionally, we perform in-vivo …

    rice Repository record for Accurate noninvasive monitoring of fetal tissue oxygenation level (opens in a new tab)

  10. Learning Without Training

    … leveraging techniques originally introduced for signal separation problems. The analogue to point sources are the supports of distributions from which data belonging to each class is sampled from. We introduce theory to unify signal separation with classification and a new algorithm which yields …

    claremont Repository record for Learning Without Training (opens in a new tab)

  11. A Temporal Encoder-Decoder Approach to Extracting Blood Volume Pulse Signal Morphology from Face Videos

    … the more difficult problem of recovering BVP signal morphology. We present a new approach that is inspired by temporal encoder-decoder architectures that have been used for audio signal separation. As input, this system accepts a temporal sequence of RGB (red, green, blue) values that have …

    vt Repository record for A Temporal Encoder-Decoder Approach to Extracting Blood Volume Pulse Signal Morphology from Face Videos (opens in a new tab)

  12. Detection of brain metabolites in magnetic resonance spectroscopy

    … magnetic resonance imaging (MRI) derives its signal from protons in water, additional and potentially important biochemical compounds are detectable in vivo within the proton spectrum. The detection and mapping of these much weaker signals is known as magnetic resonance spectroscopy or …

    mit Repository record for Detection of brain metabolites in magnetic resonance spectroscopy (opens in a new tab)

  13. Localized Kernel Methods for Signal Processing

    <p>This dissertation presents two signal processing methods using specially designed localized kernels for parameter recovery under noisy condition. The first method addresses the estimation of frequencies and amplitudes in multidimensional exponential models. It utilizes localized trigonometric …

    claremont Repository record for Localized Kernel Methods for Signal Processing (opens in a new tab)

  14. Development of In Situ Monitoring and Data-Driven Modeling for Complex Systems: Case Study on Simulant Mixtures of Nuclear Waste

    … of the waste system increases, advanced signal separation preprocessing techniques are incorporated in the modeling framework. The goal of the additional steps is to identify the contributions of the target species in complex systems, which allows for increased robustness of the …

    gatech Repository record for Development of In Situ Monitoring and Data-Driven Modeling for Complex Systems: Case Study on Simulant Mixtures of Nuclear Waste (opens in a new tab)

  15. Magnetic resonance spectroscopic imaging with 2D spectroscopy for the detection of brain metabolites

    … magnetic resonance imaging (MRI) derives its signal from protons in water, additional biochemical compounds are detectable in vivo within the proton spectrum. The detection and mapping of these much weaker signals is known as magnetic resonance spectroscopy or spectroscopic imaging. Among the …

    mit Repository record for Magnetic resonance spectroscopic imaging with 2D spectroscopy for the detection of brain metabolites (opens in a new tab)

  16. Score Estimation for Generative Modeling

    … our development around the problem of source separation, we introduce a novel algorithm inspired by maximum a posteriori estimation. This approach combines multiple levels of Gaussian smoothing with an α-posterior, enabling effective signal separation using only independent priors for the …

    mit Repository record for Score Estimation for Generative Modeling (opens in a new tab)

  17. Source characterization using linear transformations of multichannel biomagnetic recordings

    … However, the extraction of the fetal MCG signal relies on the identification and elimination of other signal contributions associated with the maternal cardiac activity or specific fetal behavioral patterns, such as fetal sucking and hiccup activity. The results of the present thesis …

    patras-thes Repository record for Source characterization using linear transformations of multichannel biomagnetic recordings (opens in a new tab)

  18. Development of a Novel Methodology for the Identification of VOC Emission Sources in Indoor Environments based on the Material Emission Signatures and Air Samples measured by PTR-MS

    … mixtures for the application and validation of a signal separation methodology and its source identification enhancement by the consideration of long-term emissions. The methodology was developed based on signal processing principles by employing the method of multiple regression least squares …

    syracuse-diss Repository record for Development of a Novel Methodology for the Identification of VOC Emission Sources in Indoor Environments based on the Material Emission Signatures and Air Samples measured by PTR-MS (opens in a new tab)

  19. High-dimensional change point detection for mean and location parameters

    … size under the null and it achieves the minimax separation rate under the sparse alternatives when $p \gg n$. Once a change point is detected, we estimate the change point location by maximizing the $\ell^{\infty}$-norm of the generalized CUSUM statistics at two different weighting scales. The …

    uiuc Repository record for High-dimensional change point detection for mean and location parameters (opens in a new tab)

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