1. Chapter 1 Fundamental Concepts

2. signalpattern of variation of a physical quantityA signal is a pattern of variation of a physical quantity as a function of time, space, distance, position, temperature, pressure, etc. independent variablesThese quantities are usually the independent variables of the function defining the signal informationA signal encodes information, which is the variation itself Signals

3. extracting, analyzing, and manipulating the informationSignal processing is the discipline concerned with extracting, analyzing, and manipulating the information carried by signals The processing method depends on the type of signal and on the nature of the information carried by the signal Signal Processing

4. type of signalThe type of signal depends on the nature of the independent variables and on the value of the function defining the signal continuous or discreteFor example, the independent variables can be continuous or discrete continuous or discrete functionLikewise, the signal can be a continuous or discrete function of the independent variables Characterization and Classification of Signals

5. real- valued functioncomplex-valued functionMoreover, the signal can be either a real- valued function or a complex-valued function scalar or one-dimensional (1-D) signalA signal consisting of a single component is called a scalar or one-dimensional (1-D) signal vector or multidimensional (M-D) signalA signal consisting of multiple components is called a vector or multidimensional (M-D) signal Characterization and Classification of Signals – Cont’d

6. Definition of Function from Calculus domain domain: set of values that t can take on range: range: set of values spanned by y independent variable dependent variable

7. Plot or Graph of a Function range domain

8. continuous-time (CT) signalA signal x(t) depending on a continuous temporal variable will be called a continuous-time (CT) signal discrete-time (DT) signalA signal x[n] depending on a discrete temporal variable will be called a discrete-time (DT) signal Continuous-Time (CT) and Discrete-Time (DT) Signals

9. Examples: CT vs. DT Signals stem(n,x)plot(t,x)

10. 1-D, real-valued, CT signal1-D, real-valued, CT signal: N-D, real-valued, CT signal:N-D, real-valued, CT signal: 1-D, complex-valued, CT signal:1-D, complex-valued, CT signal: N-D, complex-valued, CT signal: CT Signals: 1-D vs. N-D, Real vs. Complex

11. DT Signals: 1-D vs. N-D, Real vs. Complex 1-D, real-valued, DT signal1-D, real-valued, DT signal: N-D, real-valued, DT signal:N-D, real-valued, DT signal: 1-D, complex-valued, DT signal:1-D, complex-valued, DT signal: N-D, complex-valued, DT signal:

12. digital signalA DT signal whose values belong to a finite set or alphabet is called a digital signal finite-precision arithmeticSince computers work with finite-precision arithmetic, only digital signals can be numerically processed Digital Signal ProcessingDigital Signal Processing (DSP): ECE 464/564 (Liu) and ECE 567 (Lucchese) Digital Signals

13. Digital Signals: 1-D vs. N-D 1-D, real-valued, digital signal1-D, real-valued, digital signal: N-D, real-valued, digital signal:N-D, real-valued, digital signal: If, the digital signal is real, if instead at least one of the, the digital signal is complex

14. systemprocess signalsA system is any device that can process signals for analysis, synthesis, enhancement, format conversion, recording, transmission, etc. I/O characterizationA system is usually mathematically defined by the equation(s) relating input to output signals (I/O characterization) A system may have single or multiple inputs and single or multiple outputs Systems

15. Block Diagram Representation of Single-Input Single-Output (SISO) CT Systems input signal output signal

16. Block Diagram Representation of Single-Input Single-Output (SISO) DT Systems input signal output signal

17. A Hybrid SISO System: The Analog to Digital Converter (ADC) Used to convert a CT (analog) signal into a digital signal ADC

18. Block Diagram Representation of Multiple-Input Multiple-Output (MIMO) CT Systems

19. Example of 1-D, Real-Valued, Digital Signal: Digital Audio Signal

20. Example of 1-D, Real-Valued, Digital Signal with a 2-D Domain: A Digital Gray-Level Image pixel coordinates

21. Digital Gray-Level Image: Cont’d

22. Example of 3-D, Real-Valued, Digital Signal with a 2-D Domain: A Digital Color Image

23. Digital Color Image: Cont’d

24. Example of 3-D, Real-Valued, Digital Signal with a 3-D Domain: A Digital Color Video Sequence (temporal axis)

25. Differential equation (or difference equation) The convolution model The transfer function representation (Fourier transform representation) Types of input/output representations considered

26. Examples of 1-D, Real-Valued, CT Signals: Temporal Evolution of Currents and Voltages in Electrical Circuits

27. Examples of 1-D, Real-Valued, CT Signals: Temporal Evolution of Some Physical Quantities in Mechanical Systems

28. Unit-step functionUnit-step function Unit-ramp functionUnit-ramp function Continuous-Time (CT) Signals

29. Unit-Ramp and Unit-Step Functions: Some Properties (to the exception of )

30. delta functionDirac distributionA.k.a. the delta function or Dirac distribution It is defined by:It is defined by: The value is not defined, in particularThe value is not defined, in particular The Unit Impulse

31. The Unit Impulse: Graphical Interpretation A is a very large number

32. If, is the impulse with area, i.e., The Scaled Impulse K(t)

33. Properties of the Delta Function except 1) 2) sifting property (sifting property)

34. Definition: a signal is said to be periodic with period, if Notice that is also periodic with period where is any positive integer fundamental period is called the fundamental period Periodic Signals

35. Example: The Sinusoid

36. Let and be two periodic signals with periods T 1 and T 2, respectively Then, the sum is periodic only if the ratio T 1 /T 2 can be written as the ratio q/r of two integers q and r In addition, if r and q are coprime, then T=rT 1 is the fundamental period of Is the Sum of Periodic Signals Periodic?

37. Time-Shifted Signals

38. A continuous-time signal is said to be discontinuous at a point if where and, being a small positive number Points of Discontinuity

39. A signal is continuous at the point if continuous signalIf a signal is continuous at all points t, is said to be a continuous signal Continuous Signals

40. Example of Continuous Signal: The Triangular Pulse Function

41. A signal is said to be piecewise continuous if it is continuous at all except a finite or countably infinite collection of points Piecewise-Continuous Signals

42. Example of Piecewise-Continuous Signal: The Rectangular Pulse Function

43. Another Example of Piecewise- Continuous Signal: The Pulse Train Function

44. differentiableA signal is said to be differentiable at a point if the quantity has limit as independent of whether approaches 0 from above or from below derivativeIf the limit exists, has a derivative at Derivative of a Continuous-Time Signal

45. In order for to be differentiable at a point, it is necessary (but not sufficient) that be continuous at Continuous-time signals that are not continuous at all points (piecewise continuity) cannot be differentiable at all points Continuity and Differentiability

46. However, piecewise-continuous signals may have a derivative in a generalized sense Suppose that is differentiable at all except generalized derivativeThe generalized derivative of is defined to be Generalized Derivative ordinary derivative of at all except

47. Define The ordinary derivative of is 0 at all points except Therefore, the generalized derivative of is Example: Generalized Derivative of the Step Function

48. Consider the function defined as Another Example of Generalized Derivative

49. The ordinary derivative of, at all except is Its generalized derivative is Another Example of Generalized Derivative: Cont’d

51. Consider the signal This signal can be expressed in terms of the unit-step function and its time-shifts as Signals Defined Interval by Interval

52. By rearranging the terms, we can write where Signals Defined Interval by Interval: Cont’d

53. A discrete-time signal is defined only over integer values We denote such a signal by Discrete-Time (DT) Signals

54. Suppose that Example: A Discrete-Time Signal Plotted with Matlab n=-2:6; x=[0 0 1 2 1 0 –1 0 0]; stem(n,x) xlabel(‘n’) ylabel(‘x[n]’)

55. Discrete-time signals are usually obtained by sampling continuous-time signals Sampling..

56. DT Step and Ramp Functions

57. DT Unit Pulse

58. A DT signal is periodic if there exists a positive integer r such that r is called the period of the signal The fundamental period is the smallest value of r for which the signal repeats Periodic DT Signals

59. Consider the signal The signal is periodic if Recalling the periodicity of the cosine is periodic if and only if there exists a positive integer r such that for some integer k or, equivalently, that the DT frequency is such that for some positive integers k and r Example: Periodic DT Signals

60. Example: for different values of periodic signal with period aperiodic signal (with periodic envelope)

61. DT Rectangular Pulse (L must be an odd integer)

62. digital signalA digital signal is a DT signal whose values belong to a finite set or alphabet A CT signal can be converted into a digital signal by cascading the ideal sampler with a quantizer Digital Signals

63. If is a DT signal and q is a positive integer Time-Shifted Signals is the q-step right shift of is the q-step left shift of

64. Example of CT System: An RC Circuit Kirchhoff’s current law:

65. The v-i law for the capacitor is Whereas for the resistor it is RC Circuit: Cont’d

66. Constant-coefficient linear differential equationConstant-coefficient linear differential equation describing the I/O relationship if the circuit RC Circuit: Cont’d

67. Step response when R=C=1 RC Circuit: Cont’d

68. where is the drive or braking force applied to the car at time t and is the car’s position at time t Example of CT System: Car on a Level Surface Newton’s second law of motion:

69. Car on a Level Surface: Cont’d Step response when M=1 and

70. Example of CT System: Mass-Spring-Damper System

71. Mass-Spring-Damper System: Cont’d Step response when M=1, K=2, and D=0.5

72. Example of CT System: Simple Pendulum If

73. causalA system is said to be causal if, for any time t 1, the output response at time t 1 resulting from input x(t) does not depend on values of the input for t > t 1. noncausalA system is said to be noncausal if it is not causal Basic System Properties: Causality

74. Example: The Ideal Predictor

75. Example: The Ideal Delay

76. memorylessstaticA causal system is memoryless or static if, for any time t 1, the value of the output at time t 1 depends only on the value of the input at time t 1 memoryA causal system that is not memoryless is said to have memory. A system has memory if the output at time t 1 depends in general on the past values of the input x(t) for some range of values of t up to t = t 1 Memoryless Systems and Systems with Memory

77. Ideal Amplifier/AttenuatorIdeal Amplifier/Attenuator RC CircuitRC Circuit Examples

78. additiveA system is said to be additive if, for any two inputs x 1 (t) and x 2 (t), the response to the sum of inputs x 1 (t) + x 2 (t) is equal to the sum of the responses to the inputs, assuming no initial energy before the application of the inputs Basic System Properties: Additive Systems system

79. homogeneousA system is said to be homogeneous if, for any input x(t) and any scalar a, the response to the input ax(t) is equal to a times the response to x(t), assuming no energy before the application of the input Basic System Properties: Homogeneous Systems system

80. linearA system is said to be linear if it is both additive and homogeneous nonlinearA system that is not linear is said to be nonlinear Basic System Properties: Linearity system

81. Example of Nonlinear System: Circuit with a Diode

82. Example of Nonlinear System: Square-Law Device

83. Example of Linear System: The Ideal Amplifier

84. Example of Linear System: A Real Amplifier

85. time invariantA system is said to be time invariant if, for any input x(t) and any time t 1, the response to the shifted input x(t – t 1 ) is equal to y(t – t 1 ) where y(t) is the response to x(t) with zero initial energy time varyingtime variantA system that is not time invariant is said to be time varying or time variant Basic System Properties: Time Invariance system

86. Amplifier with Time-Varying GainAmplifier with Time-Varying Gain First-Order SystemFirst-Order System Examples of Time Varying Systems

87. Let x(t) and y(t) be the input and output of a CT system Let x (i) (t) and y (i) (t) denote their i-th derivatives finite dimensional lumpedThe system is said to be finite dimensional or lumped if, for some positive integer N the N-th derivative of the output at time t is equal to a function of x (i) (t) and y (i) (t) at time t for Basic System Properties: Finite Dimensionality

88. The N-th derivative of the output at time t may also depend on the i-th derivative of the input at time t for order I/O differential equationorder or dimension of the systemThe integer N is called the order of the above I/O differential equation as well as the order or dimension of the system described by such equation Basic System Properties: Finite Dimensionality – Cont’d

89. infinite dimensionalA CT system with memory is infinite dimensional if it is not finite dimensional, i.e., if it is not possible to express the N-th derivative of the output in the form indicated above for some positive integer N Example: System with DelayExample: System with Delay Basic System Properties: Finite Dimensionality – Cont’d

90. Let x[n] and y[n] be the input and output of a DT system. finite dimensionalThe system is finite dimensional if, for some positive integer N and nonnegative integer M, y[n] can be written in the form I/O difference equationorder or dimension of the systemN is called the order of the I/O difference equation as well as the order or dimension of the system described by such equation DT Finite-Dimensional Systems

91. If the N-th derivative of a CT system can be written in the form then the system is both linear and finite dimensional Basic System Properties: CT Linear Finite-Dimensional Systems

92. Basic System Properties: DT Linear Finite-Dimensional Systems If the output of a DT system can be written in the form then the system is both linear and finite dimensional

93. For a CT system it must be And, similarly, for a DT system Basic System Properties: Linear Time-Invariant Finite-Dimensional Systems

94. Some authors define the order as N Some as Some others as About the Order of Differential and Difference Equations