Compressed Sensing for Denoising in Adaptive System Identification

سال انتشار: 1391
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 1,428

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شناسه ملی سند علمی:

ICEE20_265

تاریخ نمایه سازی: 14 مرداد 1391

چکیده مقاله:

We propose a new technique for adaptive identification of sparse systems based on the compressed sensing (CS) theory. We manipulate the transmitted pilot (input signal)and the received signal such that the weights of adaptive filter approach the compressed version of the sparse system instead ofthe original system. To this end, we use random filter structure at the transmitter to form the measurement matrix according to theCS framework. The original sparse system can be reconstructed by the conventional recovery algorithms. As a result, the denoising property of CS can be deployed in the proposedmethod at the recovery stage. The experiments indicate significant performance improvement of proposed methodcompared to the conventional LMS method which directly identifies the sparse system. Furthermore, at low levels of sparsity, our method outperforms a specialized identification algorithm that promotes sparsity

نویسندگان

Seyed Hossein Hosseini

Department of Electrical Engineering, Urmia University, Urmia, Iran