.png){kind=icon}
.png){kind=icon}
Return
Tensor projection mechanism and algorithm implementation
.png){kind=icon}
PRE
AI
DOI：10.1007/s10489-021-02332-3.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper analyses the mechanism of tensor projection transformation in depth and introduces a high-efficiency original algorithm developed in a quantum computing language for forward and backward projection between multidimensional tensors and one-dimensional vectors. Additionally, the author compares this algorithm with similar methods from both the Python scientific computing package and other relative development kits in method calls and source code to demonstrate the innovation of the tensor projection algorithm. On this basis, the classical convolution operation program commonly used in machine learning has been parallelized and improved, the analysis algorithm of the Beidou communication satellite view area has been parallelized and improved, and the actual operating efficiency has been greatly improved. After verification, the tensor projection transformation successfully solves the problem of location index mapping of the entity units among different dimensions, can provide a means for optimizing the traditional model of traversal algorithm, and can have significant reference value in eigenspace transformation against a tensor field.
Keywords:
Tensor projection
Numerical algorithm
Parallelization
Quantum computation language
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.5
Papers:
7.5K
Citations:
1.7W