suppression of disturbance signal

简明释义

干扰信号抑制

英英释义

例句

1.The suppression of disturbance signal can significantly improve the performance of radar systems.

对雷达系统来说，干扰信号的抑制可以显著提升性能。

2.The research focused on methods for effective suppression of disturbance signal in biomedical applications.

该研究集中于生物医学应用中有效的干扰信号的抑制方法。

3.In advanced communication systems, the suppression of disturbance signal is crucial for maintaining clear voice quality.

在先进的通信系统中，干扰信号的抑制对于保持清晰的语音质量至关重要。

4.Engineers use filters to achieve the suppression of disturbance signal in audio processing.

工程师使用滤波器来实现音频处理中的干扰信号的抑制。

5.To enhance image quality, the suppression of disturbance signal is applied in digital cameras.

为了增强图像质量，数字相机中应用了干扰信号的抑制。

作文

In the realm of signal processing, one of the most critical challenges is the ability to filter out unwanted noise that can interfere with the desired signal. This is particularly important in various applications such as telecommunications, medical imaging, and environmental monitoring. A key concept that emerges in this context is the suppression of disturbance signal, which refers to techniques used to minimize or eliminate the impact of extraneous signals that can distort the information we wish to capture or transmit. Understanding this concept is essential for engineers and scientists alike, as it directly affects the quality and reliability of data transmission and analysis.The suppression of disturbance signal can be achieved through various methods, including filtering, adaptive algorithms, and advanced signal processing techniques. For instance, filters can be designed to allow only certain frequencies to pass while blocking others, effectively removing unwanted noise. In adaptive filtering, the system continuously adjusts its parameters based on the characteristics of the incoming signal and the noise, ensuring optimal performance in real-time scenarios.One practical example of the suppression of disturbance signal can be found in the field of medical imaging, specifically in magnetic resonance imaging (MRI). MRI machines generate detailed images of the human body, but they are also susceptible to various types of interference. By employing sophisticated algorithms to enhance the images while suppressing noise, healthcare professionals can obtain clearer and more accurate representations of internal structures, leading to better diagnoses and treatment plans.Moreover, in telecommunications, the suppression of disturbance signal plays a vital role in maintaining the integrity of data being transmitted over long distances. As signals travel through various mediums, they encounter different forms of interference, such as electromagnetic interference from other devices or atmospheric conditions. Engineers utilize coding techniques and modulation schemes to enhance signal resilience and ensure that the original message remains intact despite the presence of disturbances.In environmental monitoring, the suppression of disturbance signal is crucial for accurately measuring phenomena such as air quality or water pollution levels. Sensors deployed in these environments often pick up background noise that can skew the results. By implementing noise reduction techniques, researchers can focus on the true readings of pollutants, thereby providing more reliable data for policy-making and public health initiatives.In conclusion, the suppression of disturbance signal is a fundamental aspect of modern technology that enhances our ability to communicate, diagnose, and monitor our world effectively. As we continue to advance in fields such as artificial intelligence and machine learning, the techniques for achieving this suppression will only become more refined and essential. Understanding and mastering these concepts not only benefits professionals in technical fields but also empowers society to harness technology for improved quality of life and informed decision-making.

在信号处理领域，最关键的挑战之一是过滤掉可能干扰所需信号的噪声。这在电信、医学成像和环境监测等各种应用中尤为重要。在这种情况下，一个关键概念是干扰信号的抑制，这指的是用于最小化或消除外部信号影响的技术，这些信号可能扭曲我们希望捕获或传输的信息。理解这一概念对工程师和科学家来说至关重要，因为它直接影响数据传输和分析的质量和可靠性。干扰信号的抑制可以通过多种方法实现，包括滤波、适应性算法和先进的信号处理技术。例如，可以设计滤波器以允许某些频率通过，同时阻止其他频率，从而有效去除不必要的噪声。在适应性滤波中，系统根据输入信号和噪声的特征不断调整其参数，确保在实时场景中的最佳性能。干扰信号的抑制的一个实际例子可以在医学成像领域找到，特别是在磁共振成像（MRI）中。MRI机器生成人体的详细图像，但它们也容易受到各种类型的干扰。通过采用复杂的算法来增强图像，同时抑制噪声，医疗专业人员可以获得更清晰、更准确的内部结构表示，从而导致更好的诊断和治疗方案。此外，在电信中，干扰信号的抑制在保持远距离传输数据的完整性方面起着至关重要的作用。当信号通过各种介质传播时，它们会遇到不同形式的干扰，例如来自其他设备的电磁干扰或大气条件。工程师利用编码技术和调制方案来增强信号的抗干扰能力，确保原始信息在干扰存在的情况下仍然保持完整。在环境监测中，干扰信号的抑制对于准确测量空气质量或水污染水平至关重要。在这些环境中部署的传感器通常会捕捉到背景噪声，这可能会扭曲结果。通过实施噪声减少技术，研究人员可以专注于污染物的真实读数，从而为政策制定和公共健康倡议提供更可靠的数据。总之，干扰信号的抑制是现代技术的一个基本方面，它增强了我们有效沟通、诊断和监测世界的能力。随着我们在人工智能和机器学习等领域的不断进步，实现这种抑制的技术只会变得更加精细和重要。理解和掌握这些概念不仅有利于技术领域的专业人士，也使社会能够利用技术改善生活质量和做出明智的决策。