quantized signal

简明释义

量子化信号

英英释义

例句

1.In digital communication systems, the transmission of a quantized signal 量化信号 allows for efficient data transfer.

在数字通信系统中，传输量化信号 quantized signal可以实现高效的数据传输。

2.In image processing, a quantized signal 量化信号 can represent pixel values after digitization.

在图像处理中，量化信号 quantized signal可以表示数字化后的像素值。

3.The process of converting an analog signal into a quantized signal 量化信号 is known as quantization.

将模拟信号转换为量化信号 quantized signal的过程称为量化。

4.The quality of a quantized signal 量化信号 depends on the number of quantization levels used.

一个量化信号 quantized signal的质量取决于使用的量化级别数量。

5.Audio recordings are often stored as quantized signals 量化信号 to reduce file size.

音频录音通常作为量化信号 quantized signals存储，以减少文件大小。

作文

In the field of digital communications and signal processing, the concept of a quantized signal is fundamental. A quantized signal refers to a continuous signal that has been converted into a digital format through a process known as quantization. This process involves mapping a range of values to discrete levels, allowing for easier storage, transmission, and processing of information. Understanding quantized signals is essential for anyone interested in audio and video technology, telecommunications, and data compression.To begin with, let's explore the nature of signals. Signals can be either analog or digital. Analog signals are continuous and can take on any value within a given range. For example, sound waves are analog signals that vary continuously over time. In contrast, digital signals are discrete and consist of specific values, usually represented in binary form (0s and 1s). The transition from an analog signal to a digital one involves two key steps: sampling and quantization.Sampling is the first step, where the continuous signal is measured at regular intervals. This process captures the amplitude of the signal at specific points in time. However, sampling alone does not convert the signal into a quantized signal. After sampling, the next step is quantization, which involves rounding the sampled values to the nearest discrete level. This is where the concept of a quantized signal comes into play. Quantization can introduce errors, known as quantization noise, because the original continuous values are approximated by discrete ones. The degree of this error depends on the number of quantization levels used; more levels result in a more accurate representation of the original signal. For instance, if an audio signal is quantized using only eight levels, the resulting quantized signal may not accurately reflect the nuances of the original sound. On the other hand, using a higher number of levels, such as 256 or even 65536, can produce a much clearer and more faithful representation of the original signal.The importance of quantized signals extends beyond just audio applications. In video technology, images are also processed as quantized signals. Each pixel in an image can be thought of as a sampled and quantized version of the light intensity at that point. The quality of video compression techniques, such as JPEG or MPEG, relies heavily on how well the original continuous image can be represented as a quantized signal. Moreover, understanding quantized signals is crucial in telecommunications, where data must be transmitted efficiently over various channels. The choice of quantization levels can affect the bandwidth and overall performance of communication systems. Engineers must carefully balance the need for accurate signal representation with the constraints of data rates and storage capacity.In conclusion, the concept of a quantized signal is integral to modern digital technologies. From audio and video processing to telecommunications, the ability to convert continuous signals into discrete formats allows for efficient storage and transmission of information. By grasping the principles of sampling and quantization, one can appreciate the complexities involved in creating high-quality digital representations of the world around us. As technology continues to evolve, the role of quantized signals will undoubtedly remain a cornerstone in the development of innovative digital solutions.

在数字通信和信号处理领域，量化信号的概念是基础性的。量化信号指的是通过称为量化的过程将连续信号转换为数字格式。这一过程涉及将一系列值映射到离散水平，从而使信息的存储、传输和处理变得更为简单。理解量化信号对于任何对音频和视频技术、电信和数据压缩感兴趣的人来说都是至关重要的。首先，让我们探讨信号的性质。信号可以是模拟信号或数字信号。模拟信号是连续的，可以在给定范围内取任意值。例如，声波是随时间连续变化的模拟信号。相反，数字信号是离散的，由特定值组成，通常以二进制形式表示（0和1）。从模拟信号到数字信号的转换涉及两个关键步骤：采样和量化。采样是第一步，在此过程中，连续信号在规则间隔内被测量。这个过程捕捉了信号在特定时间点的幅度。然而，仅仅进行采样并不能将信号转换为量化信号。在采样之后，下一步是量化，这涉及将采样值四舍五入到最近的离散水平。这就是量化信号概念的来源。量化可能会引入误差，称为量化噪声，因为原始连续值被近似为离散值。这种误差的程度取决于使用的量化级数；更多的级数会导致对原始信号的更准确表示。例如，如果一个音频信号使用仅八个级别进行量化，那么得到的量化信号可能无法准确反映原始声音的细微差别。另一方面，使用更高数量级别，例如256或甚至65536，可以产生更清晰、更忠实于原始信号的表示。量化信号的重要性不仅限于音频应用。在视频技术中，图像也被处理为量化信号。图像中的每个像素可以看作是该点光强的采样和量化版本。视频压缩技术（如JPEG或MPEG）的质量在很大程度上依赖于原始连续图像如何能够作为量化信号进行表示。此外，理解量化信号在电信中至关重要，因为数据必须通过各种通道高效传输。量化级别的选择可以影响带宽和通信系统的整体性能。工程师必须仔细平衡对准确信号表示的需求与数据速率和存储容量的限制。总之，量化信号的概念是现代数字技术的基石。从音频和视频处理到电信，将连续信号转换为离散格式的能力允许有效地存储和传输信息。通过掌握采样和量化的原则，人们可以欣赏到创建高质量数字表示周围世界所涉及的复杂性。随着技术的不断发展，量化信号的作用无疑将继续成为创新数字解决方案发展的基石。