The detection of an emergency signal can be estimated by the cancellation of surrounding noise an... more The detection of an emergency signal can be estimated by the cancellation of surrounding noise and achieving the desired signal in order to alert the automobilist. The aim of the thesis is to detect the emergency signal arriving nearer to the automobilist carrying hearing aids. Recent studies show that this can be achieved by designing various kinds of fixed and adaptive beam formers. A beam former does spatial filtering in the sense that it separates two signals with overlapping frequency content originating from distinctive directions. In this contribution, robust beam former namely Wiener beam former is designed and analyzed collaboratively in a group under the consideration of hearing aid constraints such as the microphone distance. A fractionally delay (FD) are designed to get a maximally flat group delay. The studies had been carried out by comparing noise cancellation algorithms like LMS, NLMS, LLMS and RLS algorithms. By comparing Omni-directional and multi-directional micro...
The detection of an emergency signal can be estimated by the cancellation of surrounding noise an... more The detection of an emergency signal can be estimated by the cancellation of surrounding noise and achieving the desired signal in order to alert the automobilist. The aim of the thesis is to detect the emergency signal arriving nearer to the automobilist carrying hearing aids. Recent studies show that this can be achieved by designing various kinds of fixed and adaptive beam formers. A beam former does spatial filtering in the sense that it separates two signals with overlapping frequency content originating from distinctive directions. In this contribution, robust beam former namely Wiener beam former is designed and analyzed collaboratively in a group under the consideration of hearing aid constraints such as the microphone distance. A fractionally delay (FD) are designed to get a maximally flat group delay. The studies had been carried out by comparing noise cancellation algorithms like LMS, NLMS, LLMS and RLS algorithms. By comparing Omni-directional and multi-directional micro...
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Papers by Arshini Gubbala