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The process of learning models from raw data typically requires a substantial amount of user input during the model initialization phase. We present an assistive visualization system which greatly reduces the load on the users and makes the process of model initialization and refinement more efficient, problem-driven, and engaging. Utilizing a sequence segmentation task with a Hidden Markov Model...
In an library based waveform (WF) development for software defined radios, high-level performance estimation models of implementations are beneficial for converging quickly to an optimal mapping of a WF-description to a hardware platform. A model that estimates the changes in performance, e.g. bit error rate (BER), due to the configuration-parameters, e.g. input data-width, in implementations is helpful...
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