In many practical applications, systems and signals show energy concentration in a few coefficients. This prior knowledge can often be incorporated into algorithms designed for tasks such as compressive sensing and sy...
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In many practical applications, systems and signals show energy concentration in a few coefficients. This prior knowledge can often be incorporated into algorithms designed for tasks such as compressive sensing and system identification. This Letter proposes a new least mean square (lms)-basedalgorithm that exploits the hidden sparsity of the system that the adaptive filter intends to estimate. The algorithm minimises the -norm of a linear transformation of the coefficient vector, using the minimum distortion principle. Simulation results demonstrate good performance of the proposed algorithm with respect to the lmsalgorithm. In addition, a stochastic model of the advanced algorithm is proposed, which provides accurate mean-square deviation and mean-square error predictions.
An lms-based algorithm to monitor fetal and maternal heart rate in real time was implemented and evaluated on a development platform. Hardware has three modules: dsPIC30F digital signal controller, a low-noise analog ...
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ISBN:
(纸本)9781424441242
An lms-based algorithm to monitor fetal and maternal heart rate in real time was implemented and evaluated on a development platform. Hardware has three modules: dsPIC30F digital signal controller, a low-noise analog front end and a storage stage. They were evaluated using on-chip debugging tools and a patient simulator. algorithm performance was tested using simulation tools and real data. Other measures like process run-times and power consumption, were analyzed to evaluate the design feasibility. Dataset was conformed by 25 annotated records from different gestational age pregnant women. Sensitivity and accuracy were used as performance measures. In general, sensitivity was high for maternal (95.3%) and fetal (87.1%) detections. Results showed that the chosen architecture can run efficiently the algorithm processes, obtaining high detection rates under appropriate SNR conditions.
The paper presents and investigates a new lms-based algorithm for a broadband power inversion array using tapped delay line processing. In this algorithm, the signals from eachL-tap delay line are first transformed an...
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The paper presents and investigates a new lms-based algorithm for a broadband power inversion array using tapped delay line processing. In this algorithm, the signals from eachL-tap delay line are first transformed and separated intoL/2 real-and-quadrature signals, with thelth signal determining the (l−1)th derivative of the frequency response of the array. Rejection of jammers is then obtained by using the lmsalgorithm to update the processing for the first transformed signals from all the array elements, while the processing for the other signals is adjusted to constrain the frequency response of the array to be maximally flat at the null directions. Since this latter adjustment needs to be performed only sparingly and the signal transformation is simple and straightforward, the complexity of the new algorithm is comparable to that when the lmsalgorithm is used directly. However, because there is now only one group of real-and-quadrature signals that needs to be adaptively processed, the new algorithm can be significantly faster than the lmsalgorithm.
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