sequential detection

简明释义

序列检测

英英释义

例句

1.By applying sequential detection, we can enhance the accuracy of our predictive models.

通过应用顺序检测，我们可以提高预测模型的准确性。

2.In the field of robotics, sequential detection is crucial for navigating complex environments.

在机器人领域，顺序检测对于在复杂环境中导航至关重要。

3.The security system uses sequential detection to monitor movements and alert for any suspicious activity.

安全系统使用顺序检测来监控运动并对任何可疑活动发出警报。

4.The new software employs sequential detection to identify patterns in data over time.

新软件采用顺序检测来识别数据随时间变化的模式。

5.Our research focuses on improving sequential detection methods in time-series analysis.

我们的研究集中在改进时间序列分析中的顺序检测方法。

作文

In the realm of data analysis and signal processing, the term sequential detection refers to a method used to identify signals or events as they occur over time. This technique is particularly valuable in situations where decisions need to be made continuously based on incoming data. For instance, in the field of telecommunications, sequential detection can help in identifying the presence of a signal amidst background noise. By analyzing the incoming data in a stepwise manner, systems can effectively discern meaningful information from irrelevant fluctuations. The essence of sequential detection lies in its ability to process data incrementally. Instead of waiting for a complete dataset before making a decision, this method allows for real-time analysis. This is crucial in applications such as radar systems, where detecting an object’s presence quickly can be a matter of safety. In these cases, the system continuously evaluates data points and updates its detection status accordingly. Moreover, sequential detection is not limited to technical fields; it also finds applications in various industries, including finance and healthcare. For example, in finance, traders may use sequential detection to monitor stock price movements, allowing them to make informed decisions based on the latest market trends. Similarly, in healthcare, monitoring vital signs can benefit from this approach, enabling medical professionals to respond promptly to changes in a patient’s condition. The advantages of sequential detection are manifold. Firstly, it enhances responsiveness, allowing systems to react to new information as it becomes available. This immediacy is essential in environments where timing is critical. Secondly, it increases efficiency by reducing the need for extensive data collection before action can be taken. This not only saves time but also conserves resources, which is particularly important in high-stakes scenarios. However, implementing sequential detection does come with challenges. One significant hurdle is the potential for false positives, where the system mistakenly identifies a signal that is not present. To mitigate this risk, advanced algorithms and statistical models are often employed to improve accuracy. Additionally, the complexity of real-time data processing requires robust computational resources, which can be a limiting factor for some applications. In conclusion, sequential detection plays a pivotal role in modern data analysis and decision-making processes. Its ability to provide timely insights and enhance operational efficiency makes it an invaluable tool across various sectors. As technology continues to evolve, the methods and applications of sequential detection are likely to expand, further solidifying its importance in our increasingly data-driven world. Understanding and mastering this concept is essential for professionals looking to leverage real-time data effectively.

在数据分析和信号处理领域，短语sequential detection指的是一种用于识别随时间发生的信号或事件的方法。这种技术在需要根据不断输入的数据持续做出决策的情况下尤为重要。例如，在电信领域，sequential detection可以帮助识别背景噪声中的信号存在。通过逐步分析输入数据，系统可以有效地区分有意义的信息和无关的波动。

sequential detection的本质在于其增量处理数据的能力。与其在做出决策之前等待完整的数据集，不如让这种方法实现实时分析。这在雷达系统等应用中至关重要，因为快速检测物体的存在可能关乎安全。在这些情况下，系统不断评估数据点并相应更新其检测状态。

此外，sequential detection并不限于技术领域；它还在金融和医疗等各个行业中找到了应用。例如，在金融领域，交易者可能会使用sequential detection来监控股票价格变动，使他们能够基于最新市场趋势做出明智的决策。同样，在医疗保健中，监测生命体征也可以受益于这种方法，使医疗专业人员能够及时对患者状况的变化做出反应。

sequential detection的优势是多方面的。首先，它增强了响应能力，使系统能够对新信息做出反应。这种及时性在时间至关重要的环境中尤为重要。其次，它通过减少在采取行动之前对大量数据的收集需求，提高了效率。这不仅节省了时间，还节约了资源，这在高风险场景中特别重要。

然而，实施sequential detection确实面临挑战。其中一个重要障碍是误报的可能性，即系统错误地识别出不存在的信号。为了降低这种风险，通常会采用先进的算法和统计模型来提高准确性。此外，实时数据处理的复杂性要求强大的计算资源，这可能是某些应用的限制因素。

总之，sequential detection在现代数据分析和决策过程中发挥着关键作用。其提供及时洞察和提高操作效率的能力使其成为各个领域不可或缺的工具。随着技术的不断发展，sequential detection的方法和应用可能会扩展，进一步巩固其在我们日益数据驱动的世界中的重要性。理解和掌握这一概念对于希望有效利用实时数据的专业人士至关重要。