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Linear Time–Frequency Filters: On-line Algorithms and Applications
Published in Antonia Papandreou-Suppappola, Applications in Time-Frequency Signal Processing, 2018
This on-line Zadeh filter satisfies y[n] = x[n] for M[n,k] = 1. Because Equation (6.9) involves the future input samples x[n + 1], x[n + 2], …, x[n + K/2], causal operation of the Zadeh filter necessitates the introduction of a time delay of K/2 samples. At each time instant n, the algorithm requires an IDFT of length K and an inner product of two length-K vectors. Thus, the computational complexity of the on-line Zadeh filter is O(K+KlogK) operations per output sample. The delay of K/2 implies that the K/2 past impulse response vectors gn−1, gn−2,…, gn−K/2 have to be stored. In total, K2/2 + K memory locations are required (K/2 length-K impulse response vectors gi and the length-K input signal vector xn). Additional memory may be required by the fast Fourier transform (FFT) unless an in-place algorithm is used.
Fourier Methods for Signal Analysis and Processing
Published in Vijay K. Madisetti, The Digital Signal Processing Handbook, 2017
In each summation above, one of the ni’s is summed out of the expression, while at the same time a new ki is introduced. The notation is chosen to reflect this. For example, in stage 3, n0 is summed out, k2 is introduced as a new variable, and n0 is replaced by k2 in the result. The last operation, called bit reversal, is necessary to correctly locate the frequency samples X[k] in the memory. It is easy to show that if the samples are paired correctly, an in-place computation can be done by a sequence of butterfly operations. The term in-place means that each time a butterfly is to be computed, a pair of data samples is read from memory, and the new data pair produced by the butterfly calculation is written back into the memory locations where the original pair was stored, thereby overwriting the original data. An in-place algorithm is designed so that each data pair is needed for only one butterfly, and so the new results can be immediately stored on top of the old in order to minimize memory requirements.
Chip-Level Communication Services
Published in Hamidreza Ahmadian, Roman Obermaisser, Jon Perez, Distributed Real-Time Architecture for Mixed-Criticality Systems, 2018
M. Grammatikakis, H. Ahmadian, M. Coppola, S. Kavvadias, A. Mouzakitis, K. Papadimitriou, A. Papagrigoriou, P. Petrakis, V. Piperaki, M. Soulié, G. Tsamis
Notice that the number of sources corresponds to the number of “make RC traffic” blocks in each memory controller. Initial reservation of the quanta to different traffic flows at each memory controller are based on the MPEG4 rates as shown in Table 7.1. Thus, the initial reservations for the traffic sources of SDRAM IP are (3, 1, 1, 6, 1, 1, 1), with 6 corresponding to UP-SAMP and 3 to RAST (the two maximum rates). Notice that, since EWMA is in place, algorithm bandwidth reservations quickly adapt to the actual rates, especially since a small period (20 quanta) is used for all cases.
Fast Pattern Matching in Compressed Text using Wavelet Tree
Published in IETE Journal of Research, 2018
Surya Prakash Mishra, Rajesh Prasad, Gurmit Singh
We have divided our experiment in two cases. In Case 1, we keep alphabet size fixed while varying pattern size and text file size. In Case 2, we keep text size fixed while varying the pattern size and alphabet size. Text files and patterns have been created randomly. While searching a pattern inside the compressed text, all the occurrences of a particular pattern are to be reported. Tagged Huffman code is implemented without any extra space by using an in-place algorithm [42].
Particle swarm optimization algorithm for dynamic synchronization of smart grid
Published in Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2022
Asier Zulueta, Iker Azurmendi, Nerea Rey, Ekaitz Zulueta, Unai Fernandez-Gamiz
In first place, algorithm parameters must be defined: number of particles and number of iterations. The proper selection of these parameters would impact directly in the PSO performance. The bigger the number of iterations and particles, the more accurate, but at the expense of an increase of the computational cost.
Design of a modern fast Fourier transform and cache effective bit-reversal algorithm
Published in International Journal of Parallel, Emergent and Distributed Systems, 2023
Also, the in-place algorithm uses only bit more than half of the elements stored in the cache matrix buffer and by reducing unused elements it is possible to boost cache efficiency. To understand upcoming optimizations, it is necessary to understand the basics of the COBRA algorithm and matrix part transactions.