An absolute phase synchronization method based on phase-conjugation scheme is demonstrated. A repeatable phase difference regardless of restart operation and fiber route changing between the phase standard at local site and the recovered signal at the intermediate-access node is achieved. This indicates that absolute phase synchronization to arbitrary nodes along the fiber link is feasible. At the intermediate-access node, this phase difference is highly stable with a fluctuation of ±0.014 rad over 10000s. And this phase difference shows consistency within 2% of the full cycle under different situations such as restart operation and fiber route changing.

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Digital signature can be realized by using RSA algorithm.RSA is widely used in public-key cryptosystem. But running this algorithm needs lots of time and memory. This paper proposes a RSA signature algorithm to fit for the devices with low computational power. The new signature algorithm is based on complex numeric operation function. This paper expounds the fundamental principles of RSA algorithm. The realization of RSA algorithm includes the generation of RSA cryptographic key and the encryption and decryption of data. By using RSA algorithm, we can use the private key of the sender to sign the plaintext and the public key of the receiver to encrypt. For the receiver, he can use his private key to decrypt and the public key of the sender to verify the signature.

To improve the development level of intelligent dance education and choreography network technology, the research mainly focuses on the automatic formation system of continuous choreography by using the deep learning method. Firstly, it overcomes the technical difficulty that the dynamic segmentation and process segmentation of the automatic generation architecture in traditional choreography cannot achieve global optimization. Secondly, it is an automatic generation architecture for end-to-end continuous dance notation with access to temporal classifiers. Based on this, a dynamic time-stamping model is designed for frame clustering. Finally, it is concluded through experiments that the model successfully achieves high-performance movement time-stamping. And combined with continuous motion recognition technology, it realizes the refined production of continuous choreography with global motion recognition and then marks motion duration. This research effectively realizes the efficient and refined production of digital continuous choreography, provides advanced technical means for choreography education, and provides useful experience for school network choreography education.

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