电子科技大学：《生物医学信号处理 Biomedical Signal Processing》课程教学资源（教学大纲，饶妮妮）

电子科技大学：《生物医学信号处理》课程教学资源（教学大纲）

生物传感器是以固定化的生物材料作为敏感元件，与适当的转换元件结合所构成的一类传感器。生物传感器一般是在基础传感器上再耦合一个生物敏感膜，或者说生物传感器是半导体技术与生物工程技术的结合，生物敏感物质附着于膜上，或包含于膜中，被测量的物质经扩散作用进入生物敏感膜层，经分子识别，发生生物学反应（物理、化学变化），其所产生的信息可通过相应的化学或物理换能器转变成可定量、可处理、可显示的电信号，就可知道被测物质的浓度

基于传感器技术、信号处理技术和模式识别技术发展起来的电子鼻技术是过去二十年中发展最为迅速的气相分析和气体检测技术之一,它已逐渐在生物医学、环境监测、农业生产、食品检测等多个领域得到应用.电子鼻是利用对待测气体具有交叉敏感性的传感器阵列将待测气体中的混杂气味组分信息转化为与时间、成分、浓度或含量相关的可测物理信号组,利用信号采集系统输出含有待测气体特征信息的数字信号,通过模式识别系统分析数字信号得到待测气体综合气味信息和隐含特征,实现对待测气体快速、系统、准确的鉴别和分析.本文综述了电子鼻技术中的传感器技术和模式识别技术及在中国白酒品牌鉴定、风味识别、酒龄检测方面的最新研究进展;以聚合物石英压电传感器型电子鼻为例,阐明该电子鼻的技术方案及其在中国白酒检测中的应用;展望电子鼻未来研究方向

4.0 Introduction 4.1 Periodic Sampling 4.2 Frequency-Domain Representation of Sampling 4.3 Reconstruction of a Bandlimited Signal from its Samples 4.4 Discrete-Time Processing of Continuous Time signals 4.5 Continuous-time Processing of Discrete Time Signal

◆2.1 Discrete-Time Signals: Sequences ◆2.2 Discrete-Time Systems ◆2.3 Linear Time-Invariant (LTI) Systems ◆2.4 Properties of LTI Systems ◆2.5 Linear Constant-Coefficient Difference Equations ◆2.6 Frequency-Domain Representation of Discrete￾Time Signals and systems ◆2.7 Representation of Sequences by Fourier Transforms ◆2.8 Symmetry Properties of the Fourier Transform ◆2.9 Fourier Transform Theorems ◆2.10 Discrete-Time Random Signals

◆7.0 Introduction ◆7.1 Filter Specifications ◆7.2 Design of Discrete-Time IIR Filters From Continuous-Time Filters ◆7.3 Discrete-Time Butterworth, Chebyshev and Elliptic Filters ◆7.4 Frequency Transformations of Lowpass IIR Filters ◆7.5 Design of FIR Filters by Windowing ◆7.6 Examples of FIR Filters Design by the Kaiser Window Method

◆5.0 Introduction ◆5.1 Frequency Response of LTI Systems ◆5.2 System Functions For Systems Characterized by Linear Constant-coefficient Difference equation ◆5.3 Frequency Response for Rational System Functions ◆5.4 Relationship Between Magnitude and Phase ◆5.5 All-Pass System ◆5.6 Minimum-Phase Systems ◆5.7 Linear Systems with Generalized Linear Phase

6.0 Introduction 6.1 Block Diagram Representation of Linear Constant-Coefficient Difference Equations 6.2 Signal Flow Graph Representation of Linear Constant-Coefficient Difference Equations 6.3 Basic Structures for IIR Systems 6.4 Transposed Forms 6.5 Basic Network Structures for FIR Systems

◆3.0 Introduction ◆3.1 z-Transform ◆3.2 Properties of the Region of Convergence for the z-transform ◆3.3 The inverse z-Transform ◆3.4 z-Transform Properties ◆3.5 z-Transform and LTI Systems ◆3.6 the Unilateral z-Transform