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Showing 1 to 17 of 17 for “"Domain Representation"”.

  1. Advancing semantic modeling: addressing coordination, interpretability, and data scarcity in domain representation

    … and they struggle with both short documents and domains with limited data. These challenges limit their usefulness for applications such as search, recommendation, trend analysis, and domain comparison, where interpretability and adaptability are essential. This thesis develops four complementary …

    uiuc Repository record for Advancing semantic modeling: addressing coordination, interpretability, and data scarcity in domain representation (opens in a new tab)

  2. Program auto-tuning through population-based stochastic optimization

    … from the programs innate logic. In various domains, program autotuners have been developed which can automatically search for optimal program configurations using established optimization methods. OpenTuner is a general-purpose autotuner which provides a flexible search domain representation

    mit Repository record for Program auto-tuning through population-based stochastic optimization (opens in a new tab)

  3. Time Aliasing Methods of Spectrum Estimation

    … methods of spectrum estimation alter the time representation of a signal for the purpose of improving its frequency domain representation. Time aliasing allows characteristics of longer time window functions to be used with shorter DFT length. Windows designed specifically for use with time …

    byu Repository record for Time Aliasing Methods of Spectrum Estimation (opens in a new tab)

  4. Digital spectral analysis and adaptive processing techniques for phase modulated optical fiber sensors

    … relating a time or space signal to its frequency-domain representation was shown to be inadequate for mitigating the bias errors caused by harmonic distortions. A modified spectral estimation algorithm is presented to overcome some of the practical issues while maintaining the high spectral …

    vt Repository record for Digital spectral analysis and adaptive processing techniques for phase modulated optical fiber sensors (opens in a new tab)

  5. Harvesting online ontologies for ontology evolution

    Ontologies need to evolve to keep their domain representation adequate. However, the process of identifying new domain changes, and applying them to the ontology is tedious and time-consuming.<br></br><br></br> Our hypothesis is that online ontologies can provide background knowledge to decrease …

    the-open-u Repository record for Harvesting online ontologies for ontology evolution (opens in a new tab)

  6. Parameter recovery for transient signals

    … general basis. Several properties of a transient domain representation are discussed. Algorithms for computing numerically stable approximate transient spectra are additionally proposed. The inherent infinite bandwidth of a continuous-time transient signal motivates in part the development of a …

    mit Repository record for Parameter recovery for transient signals (opens in a new tab)

  7. Model Reduction for Linear Time-Varying Systems

    … In the third paper, we look at frequency-domain analysis of linear time-periodic impulse-response models. By decomposing the models into Taylor and Fourier series, we can analyze convergence properties of different truncated representations. In the fourth paper, we use the frequency-domain

    lund Repository record for Model Reduction for Linear Time-Varying Systems (opens in a new tab)

  8. Constrained Clustering for Frequency Hopping Spread Spectrum Signal Separation

    … Background knowledge derived from the time domain representation of received waveforms can improve these clustering methods with the novel application of cannot-link pairwise constraints to signal separation. For equivalent clustering accuracy, constraint-based clustering tolerates higher …

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

  9. Action-centered reasoning for probabilistic dynamic domains

    … focuses on modeling stochastic dynamic domains, using representations and algorithms that combine logical AI ideas and probabilistic methods. We introduce new tractable and highly accurate algorithms for reasoning in those complex domains. Furthermore, we apply these algorithms to tasks …

    uiuc Repository record for Action-centered reasoning for probabilistic dynamic domains (opens in a new tab)

  10. Nonlinear stochastic vibration analysis for energy harvesting and other applications

    … namely that the integral over its frequency domain representation is proportional to the oscillating mass, is derived and validated both numerically and experimentally, using a base excited cantilever beam with a nonlinear restoring force produced by magnets. Another form of excitation …

    cambridge Repository record for Nonlinear stochastic vibration analysis for energy harvesting and other applications (opens in a new tab)

  11. Reducing Multiple Access Interference in Broadband Multi-User Wireless Networks

    … by oversampling received signals in a time domain. Second, a novel circular-shift division multiple access (CSDMA) scheme for multi-carrier multi-user wireless systems is developed. In CSDMA, each symbol is first spread onto multiple orthogonal subcarriers in the frequency domain through …

    arkansas Repository record for Reducing Multiple Access Interference in Broadband Multi-User Wireless Networks (opens in a new tab)

  12. Information Processing in the Auditory Thalamus of the Echolocating Bat, Myotis Lucifugus: Implications for Fluttering Target Detection

    … sounds. Previous work has shown that the time-domain representation of sound undergoes a transformation between the inferior colliculus (IC) and the auditory cortex (AC) of the echolocating bat, Myotis lucifugus. Specifically, the tonic discharge patterns present in the IC are transformed into …

    uiuc Repository record for Information Processing in the Auditory Thalamus of the Echolocating Bat, Myotis Lucifugus: Implications for Fluttering Target Detection (opens in a new tab)

  13. Consistent description of radiation damping in transient soil-structure interaction

    … problems are characterized by an unbounded soil-domain and thus by radiation damping. This radiation damping arises due to wave propagation from the excited structure into the subsoil and may lead to a reduction of the structural response. A consistent description of this radiation damping has …

    qucosa-diss

  14. Path calibration algorithms for many-aperture fiber-linked broadband hypertelescopes

    … of visibility phase sampling from the frequency-domain representation of a direct image, this work develops and characterizes a set of algorithms for the calibration of absolute path lengths in many-aperture fiber-linked hypertelescopes using only mis-calibrated images taken at a few wavelengths, …

    mit Repository record for Path calibration algorithms for many-aperture fiber-linked broadband hypertelescopes (opens in a new tab)

  15. Design and Implementation of Complexity Reduced Digital Signal Processors for Low Power Biomedical Applications

    … since phase non-linearity may distort the time domain representation of the signal being filtered which is un-desirable effect for biopotential signals especially when the fiducial characteristics carry diagnostic importance. In the case of ECG monitoring systems the effect of the IIR filter phase …

    westminster Repository record for Design and Implementation of Complexity Reduced Digital Signal Processors for Low Power Biomedical Applications (opens in a new tab)

  16. Inference and Learning in Spiking Neural Networks for Neuromorphic Systems

    … exploit the energy-saving features such as spike domain representation and stochastic computing provided by SNNs in neuromorphic hardware, and to address the hardware limitations such as limited data precision and neuron fan-in/fan-out constraints, it is necessary to re-design a neural network …

    syracuse-diss Repository record for Inference and Learning in Spiking Neural Networks for Neuromorphic Systems (opens in a new tab)

  17. Inference And Learning In Spiking Neural Networks For Neuromorphic Systems

    … exploit the energy-saving features such as spike domain representation and stochastic computing provided by SNNs in neuromorphic hardware, and to address the hardware limitations such as limited data precision and neuron fan-in/fan-out constraints, it is necessary to re-design a neural network …

    syracuse-diss Repository record for Inference And Learning In Spiking Neural Networks For Neuromorphic Systems (opens in a new tab)