Inhalt Kapitel 1-3 angelegt
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@@ -8,3 +8,10 @@ Usually, a CI System consists out of an external processor (''audio processor'')
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\label{fig:fig_snychrony}
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\label{fig:fig_snychrony}
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\end{figure}
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\\As for any head worn hearing aid, the audio processor of a CI system does not only pick up the desired ambient audio signal, but also any sort of interference noises from different sources. This circumstance leads to a decrease in the quality of the final audio signal. Reducing this interference noise through Adaptive Noise Reduction (ANR), implemented on a low-power Digital Signal Processor (DSP), which can be powered within the electrical limitations of a CI system, is the topic of this master's thesis.
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\\As for any head worn hearing aid, the audio processor of a CI system does not only pick up the desired ambient audio signal, but also any sort of interference noises from different sources. This circumstance leads to a decrease in the quality of the final audio signal. Reducing this interference noise through Adaptive Noise Reduction (ANR), implemented on a low-power Digital Signal Processor (DSP), which can be powered within the electrical limitations of a CI system, is the topic of this master's thesis.
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\subsection{Overview of hearing aids and their role in auditory assistance}
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\subsection{Introduction to Cochlear Implant (CI) Systems and Audio Processors}
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\subsection{Problem description: Interference signals mixed with the ambient audio signals
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in Audio Processors}
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\subsection{Formulation of the objective of the thesis: Implementation of Adaptive Noise
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Reduction (ANR) on a dedicated low-power Digital Signal Processor (DSP)}
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\section{Theoretical Background}
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\subsection{Fundamentals of signal theory and transfer functions, including a simple illus-
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trative example}
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\subsection{Introduction to ANR}
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\subsection{Explanation of Finite Impulse Response (FIR) and Infinite Impulse Response
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(IIR) filters}
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\subsection{Introduction to the Least Mean Square (LMS) method for adaptive filtering}
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\subsection{Problem analysis: Signal flow diagram showing the origin of the useful signal,
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noise signal, and their coupling}
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\subsection{Derivation of the system’s transfer function based on the problem setup}
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\subsection{Example applications and high-level simulations using Python}
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\section{Hardware and low-level simulation of different algorithm approaches}
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\subsection{Hardware description}
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\subsection{System setup}
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\subsection{Low-level simulations of different algorithm approaches}
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