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the development of mathematical models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation through computer simulations
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This project focuses on developing algorithms capable of automatically identifying and categorizing mobile ringtones. This involves leveraging machine learning techniques to analyze audio signals
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imaging, based on absorption, provides good image contrast between high- and low-density materials, such as bones and soft tissue. However, it cannot distinguish subtle density differences between soft
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a focus. Traditionally, this is done through iterative algorithms (‘trial and error’). In this project, we aim to develop a radically different approach where the correct shape is computed using a 3-D
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the different actors' beliefs and intentions. We will study the properties of such explanations, present algorithms for automatically computing them as well as extensions to existing frameworks and evaluate
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applications of various sensors and actuators; solid mathematical foundation; priority will be given to those with experience in developing industrial-grade control algorithms, signal processing algorithms
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of blockchain, post-quantum cryptography, quantum algorithms, and heterogeneous quantum computing. Specifically, to achieve the main goal the project is expected to focus on three main areas: How can we support
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department supported by very different academic disciplines. We work with a multitude of Program Investigators (PIs) in departments both on the UW campus as well as worldwide. The department has gone through
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or internet browser. Internet Explorer is the browser of choice when using the site, however, if one browser doesn't seem to be working properly, switch to a different browser and/or clear your cache and
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will help to develop advanced, real-time atmospheric turbulence correction algorithms to enhance the long-range imaging quality of optical sighting systems. You will embed new knowledge