Sökning: "processing conditions"

Visar resultat 1 - 5 av 833 avhandlingar innehållade orden processing conditions.

  1. 1. Inverse problems in signal processing : Functional optimization, parameter estimation and machine learning

    Författare :Pol del Aguila Pla; Joakim Jaldén; Yonina C. Eldar; KTH; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; inverse problems; signal processing; machine learning; biomedical imaging; optimization; proximal optimization; regularization; mathematical modeling; identifiability; likelihood; logconcavity; immunoassays; convolutional coding; functional analysis; abstract inference; learned iterations; unrolled algorithms; Electrical Engineering; Elektro- och systemteknik;

    Sammanfattning : Inverse problems arise in any scientific endeavor. Indeed, it is seldom the case that our senses or basic instruments, i.e., the data, provide the answer we seek. LÄS MER

  3. 2. Model-based and matched-filterbank signal analysis

    Författare :Andreas Jakobsson; Uppsala universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; non-parametric spectral estimation; efficient implementations; array processing; parameter estimation; identifiability; subspace fitting; Signal processing; Signalbehandling; Signal Processing; Signalbehandling;

    Sammanfattning : The dissertation deals with model-based and matched-filterbank signal analysis. The matched-filterbank (MAFI) spectral estimation approach is introduced, and it is shown that both the amplitude spectrum Capon (ASC) and the amplitude and phase estimation (APES) spectral estimators can be expressed as MAFI spectral estimators. LÄS MER

  4. 3. Ultrasonic Arrays for Sensing and Beamforming of Lamb Waves

    Författare :Marcus Engholm; Tadeusz Stepinski; Paul D. Wilcox; Uppsala universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; imaging; array processing; guided waves; Lamb waves; dispersive waves; multi-modal waves; spatial filtering; mode suppression; resonant ultrasound; transducer design; direction of arrival estimation; adaptive beamforming; Signal processing; Signalbehandling; Electronic measurement and instrumentation; Elektronisk mät- och apparatteknik;

    Sammanfattning : Non-destructive testing (NDT) techniques are critical to ensure integrity and safety of engineered structures. Structural health monitoring (SHM) is considered as the next step in the field enabling continuous monitoring of structures. LÄS MER

  5. 4. Designing Space-Time Codes Using Orthogonal Designs

    Författare :Girish Ganesan; Thomas Marzetta; Uppsala universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Space-time codes; Orthogonal designs; Amicable orthogonal designs; Differential detection; Trellis codes; Turbo codes; Signal processing; Signalbehandling; Signalbehandling; Signal Processing;

    Sammanfattning : This thesis deals with coding schemes for systems with multiple transmit antennas. The problem of finding optimal transmission schemes for the case when the transmitter knows the channel and the case when the transmitter does not know the channel are considered. LÄS MER

  7. 5. Group-Sparse Regression : With Applications in Spectral Analysis and Audio Signal Processing

    Författare :Ted Kronvall; Statistical Signal Processing Group; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; sparse regression; group-sparsity; statistical modeling; regularization; hyperparameter-selection; spectral analysis; audio signal processing; classification; localization; multi-pitch estimation; chroma; convex optimization; ADMM; cyclic coordinate descent; proximal gradient;

    Sammanfattning : This doctorate thesis focuses on sparse regression, a statistical modeling tool for selecting valuable predictors in underdetermined linear models. By imposing different constraints on the structure of the variable vector in the regression problem, one obtains estimates which have sparse supports, i.e. LÄS MER