signal to noise ratio

简明释义

信噪比

英英释义

例句

1.When recording music, achieving a good signal to noise ratio 信噪比 is essential for high-quality sound.

在录制音乐时，获得良好的信号与噪声比 信噪比 对于高质量的声音至关重要。

2.The signal to noise ratio 信噪比 in this audio file is too low, making it hard to hear the vocals.

这个音频文件中的信号与噪声比 信噪比 太低，导致很难听清人声。

3.In data analysis, a high signal to noise ratio 信噪比 means that the data is more reliable.

在数据分析中，高信号与噪声比 信噪比 意味着数据更可靠。

4.The researchers measured the signal to noise ratio 信噪比 to determine the effectiveness of their new sensor.

研究人员测量了信号与噪声比 信噪比 以确定他们新传感器的有效性。

5.In telecommunications, a higher signal to noise ratio 信噪比 indicates clearer communication.

在电信中，更高的信号与噪声比 信噪比 表示更清晰的通信。

作文

In the realm of communication and information processing, the concept of signal to noise ratio plays a crucial role. Essentially, this term refers to the measure of the desired signal's strength relative to the background noise that interferes with it. A higher signal to noise ratio indicates a clearer and more discernible signal, while a lower ratio suggests that the noise is overwhelming the signal, making it difficult to extract meaningful information. This principle is not only applicable in telecommunications but also in various fields such as audio engineering, image processing, and even in everyday situations like listening to music in a noisy environment.To illustrate the importance of signal to noise ratio, consider a simple scenario: you are trying to have a conversation with a friend at a bustling café. The chatter of other patrons, the clinking of dishes, and the sound of the espresso machine create a noisy backdrop. If your voice (the signal) is loud enough compared to the surrounding noise, your friend will easily understand what you are saying. However, if the noise level rises or if you speak too softly, your words may become indistinct, leading to miscommunication. This real-life example highlights how essential a favorable signal to noise ratio is for effective communication.In the field of audio engineering, the signal to noise ratio is a vital specification for microphones, amplifiers, and recording equipment. A high signal to noise ratio ensures that recordings capture the intended sounds without interference from unwanted background noise. For instance, professional microphones designed for studio use often boast a high signal to noise ratio, allowing musicians and sound engineers to produce high-quality recordings that faithfully represent the original performance. Conversely, consumer-grade microphones may have lower ratios, resulting in recordings that are muddled and less clear.Similarly, in image processing, the signal to noise ratio is used to evaluate the quality of digital images. When capturing photos, especially in low-light conditions, noise can manifest as graininess or distortion. A camera with a high signal to noise ratio will produce clearer images with finer details, while one with a low ratio may yield images that are difficult to interpret. Photographers often seek equipment that maximizes this ratio to ensure their work is visually appealing and true to life.Moreover, the concept of signal to noise ratio extends beyond technical fields into areas such as data analysis and research. In statistics, researchers aim for a high signal to noise ratio when interpreting data sets. A strong signal (the effect or relationship being studied) should stand out against the noise (random variations or errors). This principle is critical in scientific studies where the validity of results depends on the clarity of the signal amidst potential confounding factors.In conclusion, the signal to noise ratio is a fundamental concept that permeates various aspects of our lives, from casual conversations to advanced technological applications. Understanding and optimizing this ratio can lead to improved communication, higher quality audio and visual outputs, and more reliable data interpretations. As we navigate through an increasingly noisy world, recognizing the significance of the signal to noise ratio can help us better filter out distractions and focus on what truly matters in both personal and professional contexts.

在通信和信息处理领域，信号与噪声比的概念起着至关重要的作用。这个术语本质上是指期望信号的强度与干扰信号的背景噪声之间的比例。较高的信号与噪声比表示信号更清晰、更易辨别，而较低的比例则表明噪声压倒了信号，使得提取有意义的信息变得困难。这个原理不仅适用于电信领域，还适用于音频工程、图像处理，甚至在日常情况下，比如在嘈杂环境中听音乐。为了说明信号与噪声比的重要性，考虑一个简单的场景：你试图在热闹的咖啡馆里和朋友交谈。其他顾客的闲聊声、碗碟碰撞声以及浓缩咖啡机的声音构成了嘈杂的背景。如果你的声音（信号）相对于周围的噪声足够大，你的朋友就能轻松理解你所说的话。然而，如果噪声水平上升，或者你说得太小声，你的话可能会变得模糊，从而导致误解。这个现实生活中的例子突显了良好的信号与噪声比对于有效沟通的重要性。在音频工程领域，信号与噪声比是麦克风、放大器和录音设备的重要规格。高的信号与噪声比确保录音捕捉到预期的声音，而不会受到不必要的背景噪声的干扰。例如，专业麦克风通常为录音室使用而设计，通常具有高的信号与噪声比，使音乐家和音响工程师能够制作出高质量的录音，忠实地再现原始表演。相反，消费级麦克风可能具有较低的比率，导致录音模糊且不清晰。同样，在图像处理领域，信号与噪声比用于评估数字图像的质量。在拍摄照片时，特别是在低光条件下，噪声可能表现为颗粒感或失真。具有高信号与噪声比的相机将生成更清晰的图像，细节更丰富，而具有低比率的相机可能会产生难以解读的图像。摄影师通常寻求最大化这一比率的设备，以确保他们的作品在视觉上令人愉悦并真实可靠。此外，信号与噪声比的概念超越了技术领域，延伸到数据分析和研究等领域。在统计学中，研究人员在解释数据集时力求获得高的信号与噪声比。强信号（正在研究的效应或关系）应当在噪声（随机变动或误差）中脱颖而出。这个原理在科学研究中至关重要，因为结果的有效性依赖于信号在潜在混淆因素中的清晰度。总之，信号与噪声比是一个基本概念，渗透到我们生活的各个方面，从随意的对话到先进的技术应用。理解和优化这一比率可以改善沟通，提高音频和视觉输出的质量，并使数据解释更加可靠。随着我们在一个日益嘈杂的世界中航行，认识到信号与噪声比的重要性可以帮助我们更好地过滤干扰，专注于个人和职业背景中真正重要的事物。