With the rapid development of China's market economy and the continuous deepening of system reforms, enterprises are also facing more problems while facing greater challenges. In order to deeply explore the role of intelligent signal processing in the development of enterprises in the context of 5G technology, this article uses data collection methods, questionnaire methods, and model building methods to collect data and analyze economic and institutional factors in the development of enterprises. The algorithm has been streamlined. First the impact of environmental factors in sustainable economic development is studied. The results show that, in the optimal economic growth plan, the optimal GDP is 27.65 trillion yuan, and the proportions of the three industries are 8.8%, 38.5%, and 49.7%, respectively; in the optimal pollution emission plan, the proportions of the three industries are 11.8%, 20.15%, and 65.5% respectively. In the neutral plan, the optimal GDP is 27.89 trillion yuan, and the proportions of the three industries are 8.5%, 39.7%, and 49.8%, respectively. This shows that, under the goal of pursuing the optimal environment, the economy can still be maintained. Further the advantages of the system in this article are discussed by analyzing the degree of synergy between them and the continuous growth of the enterprise; we can find that, from 2001 to 2006, the degree of synergy between enterprise technological innovation and institutional innovation has been continuously improved, and it has increased by 332.7% during this period, which shows that technological innovation, institutional innovation, and enterprise growth are coordinated development. It was basically realized that, starting from the intelligent signal processing technology, the economic model and innovation system that can develop together with the environment have been designed.
CITATION STYLE
Che, Y., & Gao, X. (2022). Sustainability and Enterprise Economic Growth Management Based on Intelligent Signal Processing. Scientific Programming, 2022. https://doi.org/10.1155/2022/4953516
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