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The computational complexity of the HNN MLSE equalizer is quadratic in the data block length and approximately independent of the CIR length for practical systems where the data block length is larger than channel memory length.
Using the Hopfield neural network (HNN) [15] as foundation, this equalizer has complexity quadratic in the data block length and approximately independent of the channel memory length for practical systems.
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However, the required RF pulse lengths are too long for practical applications.
For practical reasons, length units were considered to be in μm and were converted to hwu following the calculations.
Although the accuracy for the velocity evaluation is reduced with larger advance lengths, it is not severe for practical purposes.
A compact absolute-length measuring system is established for practical non-contact measurement based on a single-mode fiber interferometer.
However, the enhanced test set size would go beyond the computational capability for practical N lengths.
bAs discussed in [43], the information theoretic results of quasi-static fading channels match the results of actual codes for practical code lengths, e.g., Lc≃ 100 channel uses.
The computed bumper lengths are a fraction of the overall length of a locomotive and are thus feasible for practical implementation.
These skyrmions have been limited to sizes well over 100 nm, making them ill-suited for practical applications and, at these length scales, their claim as skyrmions is still controversial10,15,16.
Memory requirements for parallel architectures capable of supporting long length codes are feasible, but hard to achieve for practical reasons on a VLSI approach.
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