Analog to Digital Conversion and Data Compression

系统的基本理论和设计算法的发展 其将模拟数据转换成数字表示。 的示例 主要关注的是过采样模数转换器（ADC） 和矢量量化系统。 后者强调低利率 通信和数据存储系统，其中PI已 过去的重大贡献。 前者最近强调， 利用标量反馈开发了高速ADC结构 二进制量化器的采样率远高于奈奎斯特速率。 另一个研究课题是这些系统之间的相互作用，例如。 G.将过采样ADC前端用于数据压缩系统 使用矢量量化。 这项工作的主要应用领域是 语音传输和识别。 信号主要以模拟形式存在，因此先于数字处理 它们必须被采样并转换为有限长度的计算机字， 这个过程叫做量子化。 这项任务是由所谓的 模数转换器（ADC）。 PI带来了新的数学 分析了过采样ADC的性能，特别是 有吸引力的类量化器从实施的角度来看。

Both fundamental theory and design algorithms are developed for systems which convert analog data into digital representation. The examples of principal interest are oversampled analog-to-digital converters (ADC) and vector quantization systems. The latter emphasizes low-rate communications and data storage systems where the PI has made significant contributions in the past. The former emphasizes recently developed architectures for high rate ADC by using scalar feedback binary quantizers at a sampling rate much higher than the Nyquist rate. An additional research topic is the interplay between these systems, e. g. the use of an oversampled ADC front end to a data compression system using vector quantization. The main application area for this work is speech transmission and recognition. Signals exist mainly in analog form, thus prior to digital processing they must be sampled and converted to finite-length computer words by a process called quantization. This task is performed by the so-called analog-to-digital converter (ADC). The PI brings new mathematical methods to bear on the analysis of oversampled ADC's, a particularly attractive class of quantizers from the implementation point of view.