mean-square value

简明释义

均方值

英英释义

例句

1.To improve audio quality, we analyze the mean-square value 均方值 of sound signals.

为了提高音频质量，我们分析声音信号的均方值 mean-square value。

2.The calculation of the mean-square value 均方值 is essential in signal processing.

在信号处理中，均方值 mean-square value 的计算是至关重要的。

3.The mean-square value 均方值 is often used in control systems to minimize error.

在控制系统中，均方值 mean-square value 常用于最小化误差。

4.In statistics, the mean-square value 均方值 helps to determine the variance of a dataset.

在统计学中，均方值 mean-square value 有助于确定数据集的方差。

5.Engineers often use the mean-square value 均方值 to assess the performance of electrical circuits.

工程师通常使用均方值 mean-square value 来评估电路的性能。

作文

In the realm of statistics and signal processing, the concept of mean-square value plays a pivotal role in evaluating the characteristics of signals. The mean-square value, or the average of the squares of a set of values, provides crucial insights into the energy and power of a signal. This is particularly important in fields such as electrical engineering, where understanding the strength and stability of signals is essential for effective communication and data transmission.To illustrate the significance of the mean-square value, consider a simple example involving a discrete-time signal represented by a series of numerical values. Suppose we have a signal with the following values: 2, -3, 4, and 1. To calculate the mean-square value, we first square each of these values: 2² = 4, (-3)² = 9, 4² = 16, and 1² = 1. Next, we find the average of these squared values by summing them up (4 + 9 + 16 + 1 = 30) and then dividing by the number of values (30 / 4 = 7.5). Therefore, the mean-square value of this signal is 7.5.This calculation demonstrates how the mean-square value encapsulates the overall magnitude of the signal, providing a single metric that reflects its energy content. In practical applications, engineers often use the mean-square value to assess the performance of various systems. For instance, in audio processing, the mean-square value can help determine the loudness of a sound wave, allowing for adjustments to be made to ensure optimal listening experiences.Moreover, the mean-square value is not only limited to electrical signals; it can be applied in various domains such as finance, where it helps in risk assessment and portfolio management. By analyzing the mean-square value of returns on investments, financial analysts can better understand the volatility and potential risks associated with different assets. This quantitative measure aids in making informed decisions that balance risk and reward.In summary, the mean-square value serves as a fundamental tool in both theoretical and practical applications across multiple disciplines. Its ability to provide a concise representation of a signal's energy makes it invaluable in engineering, finance, and beyond. Understanding and utilizing the mean-square value allows professionals to enhance their analyses and optimize their systems effectively. As technology continues to evolve, the importance of such statistical measures will only grow, highlighting the need for ongoing education and application of concepts like the mean-square value in real-world scenarios.

在统计学和信号处理领域，均方值的概念在评估信号特征方面发挥着关键作用。均方值，即一组值的平方平均数，提供了有关信号能量和功率的重要见解。这在电气工程等领域尤为重要，因为了解信号的强度和稳定性对于有效的通信和数据传输至关重要。为了说明均方值的重要性，考虑一个涉及离散时间信号的简单例子，该信号由一系列数值表示。假设我们有一个信号，其值为：2，-3，4和1。要计算均方值，我们首先对这些值进行平方：2² = 4，(-3)² = 9，4² = 16，1² = 1。接下来，我们通过将这些平方值相加（4 + 9 + 16 + 1 = 30），然后除以值的数量来找到这些平方值的平均值（30 / 4 = 7.5）。因此，该信号的均方值为7.5。这个计算展示了均方值如何概括信号的整体幅度，提供一个反映其能量内容的单一指标。在实际应用中，工程师经常使用均方值来评估各种系统的性能。例如，在音频处理过程中，均方值可以帮助确定声波的响度，从而进行调整以确保最佳的听觉体验。此外，均方值不仅限于电信号；它还可以应用于金融领域，在那里它有助于风险评估和投资组合管理。通过分析投资回报的均方值，金融分析师可以更好地理解与不同资产相关的波动性和潜在风险。这种定量度量有助于做出平衡风险与回报的明智决策。总之，均方值在多个学科的理论和实践应用中都是一个基本工具。它能够提供信号能量的简明表示，使其在工程、金融等领域不可或缺。理解和利用均方值使专业人士能够增强他们的分析能力，并有效优化他们的系统。随着技术的不断发展，这种统计度量的重要性只会增加，突显了在现实场景中持续教育和应用诸如均方值等概念的必要性。