5.1 非周期序列的傅里叶变换 5.2 非周期序列傅里叶变换的性质 5.3 非周期序列傅里叶变换与Z变换的关系 5.4 离散时间系统的频率特性 5.5 离散时间系统的频域分析 5.6 序列的希尔伯特变换 5.7 因果序列频谱的实部与虚部的约束关系 5.8 线性位不变全通系统和线性位不变因果稳定

提出一种快速傅里叶变换(FFT)的改进算法,该算法利用FFT的衰减特性,只需要对FFT算法做简单的变换,就可以有效地消除频谱泄漏分量,实现非整数次谐波的精确检测,克服了传统FFT的缺陷.该算法与加窗体FFT相比,具有相近的特性,在算法构造方面又比加窗体FFT算法更简单,因此该算法更加适合应用于存储资源有限的微处理器上.为证明该算法应用于微处理器的方便性,设计了一套基于数字信号处理(DSP)的谐波检测装置,并对该算法进行了验证

§2.1 Discrete-Time Signals: Time-Domain Representation §2.2 Operations on Sequences §2.3 Basic Sequences §2.4 The Sampling Process §2.5 Discrete-Time Systems §2.6 Time-Domain Characterization of LTI Discrete-Time System §2.7 Classification of LTI Discrete-Time Systems §2.8 Correlation of Signals

§4.1 LTI Discrete-Time Systems in the Transform Domain §4.2 The Frequency Response §4.3 Frequency Response Computation Using MATLAB §4.4 The Concept of Filtering §4.5 Phase and Group Delays §4.6 Frequency Response of the LTI Discrete-Time System §4.7 The Transfer Function §4.8 The Transfer Function §4.9 Frequency Response from Transfer Function §4.10 Types of Transfer Functions §4.11 Linear-Phase FIR Transfer Functions §4.12 Allpass Transfer Function §4.13 Minimum-Phase and Maximum-Phase Transfer Functions

§7.1 Digital Filter Specifications §7.2 Selection of Filter Type §7.3 Digital Filter Design: Basic Approaches §7.4 IIR Digital Filter Design: Bilinear Transformation Method §7.5 IIR Highpass, Bandpass, and Bandstop Digital Filter Design §7.6 Fixed Window Functions §7.7 FIR Filter Design Example

§5.1 Digital Processing of Continuous-Time Signals §5.2 Sampling of Continuous-time Signals §5.3 Effect of Sampling in the Frequency Domain §5.4 Recovery of the Analog Signal §5.5 Implication of the Sampling Process §5.6 Sampling of Bandpass Signals §5.7 Analog Lowpass Filter Specifications §5.8 Analog Lowpass Filter Design

主要对数字信号处理器（DSP, Digital Signal Processor ）进行简要介绍。 ◼ 1.1 DSP的基本概念 ◼ 1.2 DSP芯片的发展、特点、分类 ◼ 1.3 DSP产品概况

➢9.1 数字信号处理算法的DSP实现 ➢9.2 C54x应用系统设计实例 ➢9.3 DSP系统的调试与抗干扰措施

 S1. Introduction  S2. Conventional Kalman filter  S3. Example  S4. RLS and Kalman filtering  S5. Square-root information filter  S6. Square-root covariance filter  Better numerical properties than the conventional one  The square-root RLS algorithms are special cases

2.1 启动和退出MATLAB 11 2.2 MATLAB中矩阵和多维矩阵介绍 12 2.3 MATLAB中的变量 16 2.4 算术表达式和数学函数 19 2.5 计算浮点运算次数和时间管理 25 2.6 输出格式 27 2.7 帮助命令和示范 28 2.8 保存和装载 31 2.9 命令文件和函数文件 32