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Numerical and statistical analysis using Microsoft Excel
Published in Tariq Muneer, Jorge Kubie, Thomas Grassie, Heat Transfer, 2012
Tariq Muneer, Jorge Kubie, Thomas Grassie
Excel provides a very useful facility for creating lookup tables. Excel’s lookup function is based on the linear interpolation method as described above. Through the lookup facility the user may find one piece of information that is based on another piece of information. A lookup table consists of a column or row of ascending values, called ‘compare values’, and corresponding data for each compare value. This is demonstrated in worksheet Properties of the workbook Ex02-05-02.xls, which gives the thermophysical properties for air. In this illustration, the first column (temperature of the gas) contains data for the compare values. The corresponding data are the thermophysical property values.
Memories
Published in Geoff Lewis, Communications Technology Handbook, 2013
Content addressable memory (CAM). A conventional look-up table uses an address to locate a data item. The CAM operates in the reverse way. A data search word is loaded into a latch, the address count is cycled and a comparator is used to locate a match between memory locations and the latch contents. When a match is found, the corresponding address is loaded into a snapshot register. If multiple matches are found, the lowest address is indicated.
Complexity reduction of explicit MPC based on fuzzy reshaped polyhedrons for use in industrial controllers
Published in International Journal of Systems Science, 2023
Nematollah Changizi, Karim Salahshoor, Mehdi Siahi
Given all these advantages, EMPC seems to be more practical and reliable for embedded systems. With these advantages, EMPC has entered the industry. See the comprehensive overview in Oberdieck et al. (2016) for details on the successful testing of this algorithm. EMPC algorithm suffers from some drawbacks. As matter of fact, there is a trade-off between simple practical implementation and a complicated look-up table that needs storage space. In particular, the entire feedback structure of EMPC often consumes hundreds of kilobytes to several megabytes (Honek et al., 2015). This amount of memory can exceed the capabilities of embedded hardware, especially when there are multiple feedback loops throughout the control system. The computational hardware and memory required to store the lookup tables are directly proportional to the number of control regions that can grow with the number of system states, control inputs, predictions, and control ranges. However, this fact often exceeds practical limits (Kvasnica et al., 2019) and complicates the use of these controllers in models with uncertainty (Rodríguez-Ayerbe & Olaru, 2013).
Rapid thickness mapping of free-standing smectic films using colour information of reflected light II: real-time areal mapping using lookup table scheme
Published in Liquid Crystals, 2022
In order to quantify the improvement of computational efficiency made by the lookup table scheme, we have examined the execution time of the thickness determination routine for a wide range of data sizes. The results shown in Figure 8 indicate that the lookup table scheme always outperforms the direct calculation. While the execution time of the direct calculation increases linearly with the data size over 10,000, that of the lookup table scheme increases much more slowly. The lookup table scheme becomes increasingly more advantageous for larger data sets. For one-million-pixel data, the lookup table scheme takes only 150 ms to complete, compared to 50 s for direct calculations. At this point, the lookup table is 350 times faster, and the advantage grows further as the data size increases. In the present MATLAB code, the overhead time for I/O processing, such as image acquisition from the camera and data transfer between hard drives, is about 1.5 s. Therefore, even at one-million-pixel data size, the CPU execution time is still a minor contribution in the case of the lookup table scheme. Less than 2 s of total processing time per one full-size image makes the present method practically suitable for quasi-real-time thickness mapping of large images.