| Literature DB >> 35785091 |
Lijun Zhang1, Shaojin Wang1, Xinhua Zhu1, Xiaohui Guo1, Yuanbing Gu1.
Abstract
Multimodal orbital angular momentum is a research hotspot in the field of electromagnetic wave communication. How to accurately detect and identify multimodal orbital angular momentum data is a current academic problem. Based on the theory of mechanically reconfigurable arrays and neural networks, the purity, detection method, and transmission and reception of orbital angular momentum vortex waves are modeled in this paper. Through the network identification of the dynamic model of the three-degree-of-freedom reconfigurable manipulator, the paper takes the identification result and the control input of the single neuron PID as the input of the system control torque of the manipulator and realizes the reconfigurable manipulator. In the simulation process, the local approximation effect of the nonlinear control system used is very ideal. The single neuron PID controller overcomes the shortcomings of time-consuming and unsatisfactory control accuracy caused by the constant parameter of the traditional PID controller and realizes the circular loop. On the other hand, at the point of interest of the human eye, its resolution value is the largest, and its value gradually decreases as the distance from the pit increases. The experimental results show that the three-transmitting and three-receiving orbital angular momentum vortex wave transceiver system based on the mechanically reconfigurable array and neural network theory is relatively complete, and the transmission coefficient between the same modes reaches 0.827, which is much higher than that between different modes. On this basis, the modal purity, detection method, and reception of orbital angular momentum are studied accordingly. At the same time, the damage to the microscopic particles can be greatly reduced. At the same time, the information delay is reduced to 8.25%, which effectively improves the isolation characteristics of different modal orbital angular momentum channels and promotes the communication transmission of multimodal signals.Entities:
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Year: 2022 PMID: 35785091 PMCID: PMC9246632 DOI: 10.1155/2022/3224490
Source DB: PubMed Journal: Comput Intell Neurosci
Reconfigurable array description.
| Multiplexed index | The configuration plane | Mechanical kinematics | Rotary joint case | 3D analysis range |
|---|---|---|---|---|
|
| 11.77 | Connection module | 0.87 | [−1, 1] |
|
| 32.08 | Rocking module | 0.40 | [−1.21, 0.981] |
|
| 48.34 | Rocking module | 0.45 | [−1, 1.224] |
|
| 39.40 | Combination module | 0.77 | [−0.341, 1.1] |
|
| 46.61 | Connection module | 0.43 | [−0.31, 1.21] |
|
| 44.54 | Connection module | 0.11 | [−1.21, 1.51] |
|
| 28.23 | Combination module | 0.12 | [−0.571, 0.981] |
|
| 10.82 | Combination module | 0.038 | [−0.812, 1.114] |
Figure 13D analysis of mechanical kinematics rotary joint.
Figure 2Neural network iterative hierarchy topology.
Figure 3Plane distribution of network data nonlinear configuration.
Figure 4Two-dimensional distribution of mechanically reconfigurable array configuration plane division.
Multimodal orbital angular momentum algorithm steps.
| Algorithm step number | Multimodal orbital angular content |
|---|---|
| In the complex configuration | Static int interspacef = brick_width; |
| For the robot designer | Node_pos = [(1, 0), (0, 1), (2, 1), (1, 2)] |
| The d-h algorithm provides | Bbox_args = dict(boxstyle = “round”) |
| A Θ( | Head and tail patch, respectively. |
| In the configuration of the min.( | Xycoords: str, artist, transform |
| Posture of adjacent joint | Import matplotlib.pyplot as plt |
| In order to find the position max( | Import numpy as np |
| For finding | From matplotlib.lines import line2d |
|
| Arrowprops = dict(patcha = an1) |
|
| Patchb = an2, matplotlib.patch. |
|
| Connectionstyle = “arc3,rad = 0.2″ |
| Joint configuration and | #color = “red”, patch instance |
Figure 5Normalized orbital angular momentum data of planar single-arm helix.
Orbital angular momentum parameters table.
| Momentum parameter symbol | Physical meaning analysis |
|---|---|
|
| Vortex beam real part |
|
| Vortex beam imaginary part |
|
| Coordinate direction |
|
| Coordinate direction |
|
| Coordinate direction |
| FBG | Fiber Bragg grating |
| FM | Frequency modulation |
| TRL | Thru reflect line |
| HFSS | High-frequency structure simulator |
| PEC | Perfect electrical conductor |
Figure 6Inverse solution distribution of mechanically reconfigurable array function.
Figure 7Multimodal orbital angular momentum logic loop.
Figure 8Parameter distribution of orbital angular momentum electric field amplitude characteristic.
Figure 9Orbital angular momentum modal value vortex electromagnetic wave gain distribution.