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Signal and Systems Introduction to Signals and Systems Introduction to Signals and Systems Introduction to Signals and Systems as related to Engineering Modeling of physical signals by mathematical functions Modeling physical systems by mathematical equations Solving mathematical equations when excited by the input functions/signals. 23 May 2017 Veton Këpuska 2 Modeling Engineers model two distinct physical phenomena: 1. Signals are modeled by mathematical functions. 2. Physical systems are modeled by mathematical equations. 23 May 2017 Veton Këpuska 3 What are Signals? 23 May 2017 Veton Këpuska 4 Signals Signals, x(t), are typically real functions of one independent variable that typically represents time; t. Time t can assume all real values: -∞ < t < ∞, Function x(t) is typically a real function. 23 May 2017 Veton Këpuska 5 Example of Signals: Speech 23 May 2017 Veton Këpuska 6 Example of Signals EKG: 23 May 2017 Veton Këpuska 7 Example of Signals: EEC 23 May 2017 Veton Këpuska 8 Categories of Signals Signals can be: 1. Continuous, or 2. Discrete: 23 May 2017 T – sampling rate f – sampling frequency – 1/T – radial sampling frequency – 2f= 2/T Veton Këpuska 9 Signal Processing Signals are often corrupted by noise. s(t) = x(t)+n(t) Deterministic signal Want to ‘filter’ the measured signal s(t) to remove undesired noise effects n(t). Need to retrieve x(t). Corrupting, stochastic noise signal Signal Processing 23 May 2017 Veton Këpuska 10 What is a System? 23 May 2017 Veton Këpuska 11 Modeling Examples Human Speech Production is driven by air (input signal) and produces sound/speech (output signal) Voltage (signal) of a RLC circuit Music (signal) produced by a musical instrument Radio (system) converts radio frequency (input signal) to sound (output signal) 23 May 2017 Veton Këpuska 12 Speech Production Human vocal tract as a system: Driven by air (as input signal) Produces Sound/Speech (as output signal) It is modeled by Vocal tract transfer function: Wave equations, Sound propagation in a uniform acoustic tube Representing the vocal tract with simple acoustic tubes Representing the vocal tract with multiple uniform tubes 23 May 2017 Veton Këpuska 13 Anatomical Structures for Speech Production 23 May 2017 Veton Këpuska 14 Uniform Tube Model cos l x c u x, t U g e jt cos l c c sin l x c p x, t j U g e jt A cos l c Volume velocity, denoted as u(x,t), is defined as the rate of flow of air particles perpendicularly through a specified area. Pressure, denoted as p(x,t), and u(0, t ) U g ()e 23 May 2017 Veton Këpuska jt 15 RLC Circuit L R i(t) C v(t) t di (t ) 1 L Ri (t ) i ( )d v(t ) dt C Voltage, v(t) input signal Current, i(t) output signal Inductance, L (parameter of the system) Resistance, R (parameter of the system) Capacitance, C (parameter of the system) 23 May 2017 Veton Këpuska 16 Newton’s Second Law in Physics 2 d x(t ) f (t ) M dt 2 The above equation is the model of a physical system that relates an object’s motion: x(t), object’s mass: M with a force f(t) applied to it: f(t), and x(t) are models of physical signals. The equation is the model of the physical system. 23 May 2017 Veton Këpuska 17 What is a System? A system can be a collection of interconnected components: Physical Devices and/or Processors We typically think of a system as having terminals for access to the system: Inputs and Outputs 23 May 2017 Veton Këpuska 18 Example: Single Input/Single Output (SISO) System Electrical Network Vin + Vout - + - Multiple Input/Multiple Output (MIMO) System x1 (t) x2 (t) System … … xp (t) 23 May 2017 y1 (t) y2 (t) yp (t) Veton Këpuska 19 Example: Alternate Block Diagram Representation of a Multiple Input/Multiple Output (MIMO) System x(t) System x1 t x t 2 xt x p t p1 23 May 2017 y(t) y1 t y t 2 y t yq t Veton Këpuska q1 20 System Modeling Physical System Mathematical Model Model Analysis Design Procedure Model Simulation 23 May 2017 Veton Këpuska 21 Model Types 1. Input-Output Description Frequency-Domain Representations: Transfer Function - Typically used on ideal Linear-Time-Invariant Systems Fourier Transform Representation Time-Domain Representations Differential/Difference Equations Convolution Models 2. State-Space Description Time-Domain Representation 23 May 2017 Veton Këpuska 22 Model Types 1. Continuous Models 2. Discrete Models 23 May 2017 Veton Këpuska 23 End 23 May 2017 Veton Këpuska 24