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Lin, Y. A filter bank is said to be under-decimated if the number of channels is more than the decimation ratio in the subbands. A maximally decimated filter bank is well known for its application in subband coding.
Of the above-mentioned forms of radio frequency RF technology, UWB is considered one of the most accurate approaches because it can provide positioning estimates with centimeter-level accuracy. However, it is not yet known whether UWB can also offer such accurate position estimates during strenuous dynamic activities in which moves are characterized by fast changes in direction and velocity. To answer this question, this paper investigates the capabilities of UWB indoor localization systems for tracking athletes during their complex and most of the time unpredictable movements. To this end, we analyze the impact of on-body tag placement locations and human movement patterns on localization accuracy and communication reliability.
Another application of maximally decimated filter banks is in block filtering. Convolution through block filtering has the advantages that parallelism is increased and data are processed at a lower rate.
However, the computational complexity is comparable to that of direct convolution. More recently, another type of filter bank convolver has been developed.
In this scheme, the convolution is performed in the subbands. Quantization and bit allocation of subband signals are based on signal variance, as in subband coding. Consequently, for a fixed rate, the result of convolution is more accurate than is direct convolution.
As well as expanding on previous works where we used a variant of Markov chain Monte Carlo MCMCcalled Metropolis-Hastings Monte Carlo, with simulated annealing, we introduce a new search method based on frequency annealing which leads to a more rapid and robust detection. We compare the two search methods on systems where we do and do not see the merger of the black holes.
This type of filter bank convolver also enjoys the advantages of block filtering, parallelism, and a lower working rate. Nevertheless, like block filtering, there is no computational saving.
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In this article, under-decimated systems are introduced to solve the problem. The new system is decimated only by half the number of channels.
Two types of filter banks can be used in the under-decimated system: the discrete Fourier transform DFT filter banks and the cosine modulated filter banks. They are well known for their low complexity.
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In both cases, the system is approximately alias free, and the overall response is equivalent to a tunable multilevel filter. Properties of the DFT filter banks and the cosine modulated filter banks can be exploited to simultaneously achieve parallelism, computational saving, and a lower working rate.
Furthermore, for both systems, the implementation cost of the analysis or synthesis bank is comparable to that of one prototype filter plus some low-complexity modulation matrices. We demonstrate our techniques by automatically generating input filters from vulnerable binary programs.
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