基于CSD编码技术的FIR滤波器实现方案.pdf
在图像处理、语音识别等数字信号处理中,数字 引言 滤波器占有重要的地位,其性能对系统有直接的影响。随着系统在宽带、高速、实时信号处理上要求的提高,对滤波器的处理速度、性能等也提出更高的要求本文从FIR滤波器的系数考虑,采用CSD编码,对FIR数字滤波器进行优化设计。
在图像处理、语音识别等数字信号处理中,数字 引言 滤波器占有重要的地位,其性能对系统有直接的影响。随着系统在宽带、高速、实时信号处理上要求的提高,对滤波器的处理速度、性能等也提出更高的要求本文从FIR滤波器的系数考虑,采用CSD编码,对FIR数字滤波器进行优化设计。
The sigma delta conversion technique has been in existence for many years, but recent technological advances now make the devices practical and their use is becoming widespread. The converters have found homes in such applications as communications systems, consumer and professional audio, industrial weight scales, and precision measurement devices. The key feature of these converters is that they are the only low cost conversion method which provides both high dynamic range and flexibility in converting low bandwidth input signals. This application note is intended to give an engineer with little or no sigma delta background an overview of how a sigma delta converter works
Delta-sigma analog-to-digital converters (ADCs) are fascinating—almost mythical in their ability to support low- to medium-speed and high-resolution applications. They take advantage of the speed of analog circuits, along with the robustness of digital circuits. They also reduce the amount of analog circuitry used in the converter. More importantly, the analog parts of the circuit don’t need to be very accurate. Of course, the digital blocks then must work at higher sampling clocks and, thus, consume more power.