Sökning: "deep space network"

Visar resultat 21 - 25 av 87 uppsatser innehållade orden deep space network.

  1. 21. Towards Deep Learning Accelerated Sparse Bayesian Frequency Estimation

    Master-uppsats, Lunds universitet/Matematisk statistik

    Författare :Mika Persson; [2022]
    Nyckelord :Bayesian Statistics; Deep Learning; Frequency Estimation; Generative Adversarial Networks; Artificial Neural Networks; Statistical Modelling; Mathematics and Statistics;

    Sammanfattning : The Discrete Fourier Transform is the simplest way to obtain the spectrum of a discrete complex signal. This thesis concerns the case when the signal is known to contain a small (unknown) number of frequencies, not limited to the discrete Fourier frequencies, embedded in complex Gaussian noise. LÄS MER

  3. 22. Data-Driven Motion Planning : With Application for Heavy Duty Vehicles

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Oscar Palfelt; [2022]
    Nyckelord :Motion planning; Deep learning; Autonomous driving; Nonuniform sampling; Rörelseplanering; Djupinlärning; Autonom körning; Ojämn provtagning;

    Sammanfattning : Motion planning consists of finding a feasible path of an object between an initial state and a goal state, and commonly constitutes a sub-system of a larger autonomous system. Motion planners that utilize sampling-based algorithms create an implicit representation of the search space via sampling said search space. LÄS MER

  4. 23. Inverse Uncertainty Quantification for Sounding Rocket Dispersion

    Master-uppsats, KTH/Matematik (Avd.)

    Författare :Tove Ågren; [2022]
    Nyckelord :Uncertainty quantification; Bayesian inference; Rocket dispersion; Neural networks; Markov Chain Monte Carlo.; Osäkerhetskvantifiering; Bayesiansk inferens; Raketspridning; Neurala nätverk; Markovkedje-Monte Carlo;

    Sammanfattning : Sounding rocket impact points are subject to dispersion due to uncertainties in simulation model parameters and perturbations of the rocket trajectory during flight. Estimating the area of dispersion assumes that associated model uncertainties and magnitude of perturbations have already been inferred. LÄS MER

  5. 24. Investigating Machine Learning for verification of AMBA APB protocol.

    Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

    Författare :Abhiram Srisai Kishore; Mohammed Wasim; [2022]
    Nyckelord :Machine learning; SOC Verification; AMBA; Neural Networks; Deep Learning; Assertions.; Technology and Engineering;

    Sammanfattning : It is a well-known fact that in any Application Specific Integrated Circuit (ASIC) design, verification consumes most time and resources. And when it comes to huge designs, finding bugs can be tedious given the area and the complexity. As per Moore’s law, the design complexity is increasing exponentially due to the growing demand for performance. LÄS MER

  7. 25. Representation learning for single cell morphological phenotyping

    Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för fysik

    Författare :Andreas Nenner; [2022]
    Nyckelord :Deep learning; Image-based profiling;

    Sammanfattning : Preclinical research for developing new drugs is a long and expensive procedure. Experiments relying on image acquisition and analysis tend to be low throughput and use reporter systems that may influence the studied cells. LÄS MER