1. Time - Domain Analysis Of Discrete - Time Systems The first half of Chapter 3

2. 3.1. Introduction Discrete-Time Signal Discrete-Time Signal A Sequence of numbers  inherently Discrete-Time  sampling Continuous-Time signals, ex) A Sequence of numbers  inherently Discrete-Time  sampling Continuous-Time signals, ex) Discrete-Time System Discrete-Time System  Inputs and outputs are Discrete-Time signals.  A Discrete-Time(DT) signal is a sequence of numbers  DT system processes a sequence of numbers to yield another sequence.  Inputs and outputs are Discrete-Time signals.  A Discrete-Time(DT) signal is a sequence of numbers  DT system processes a sequence of numbers to yield another sequence. 2 Signal and System II 3.1-0 Discrete signals and systems

3. 3.1. Introduction Signal and System II 3 Discrete-Time Signal by sampling CT signal Discrete-Time Signal by sampling CT signal T = 0.1 : Sampling interval n : Discrete variable taking on integer values.  conversion to process CT signal by DT system. T = 0.1 : Sampling interval n : Discrete variable taking on integer values.  conversion to process CT signal by DT system.

4. 3.1. Introduction Signal and System II 4 3.1-1 Size of DT Signal  Energy Signal (3.1) Signal amp. 0 as  Power Signal (3.2) for periodic signals, one period time averaging. A DT signal can either be an energy signal or power signal Some signals are neither energy nor power signal.  Energy Signal (3.1) Signal amp. 0 as  Power Signal (3.2) for periodic signals, one period time averaging. A DT signal can either be an energy signal or power signal Some signals are neither energy nor power signal.

5. 3.1. Introduction Signal and System II 5  Example 3.1 (1)

6. 3.1. Introduction Signal and System II 6  Example 3.1 (2)

7. 3.2. Useful Signal Operations Signal and System II 7  Shifting   Shifting  Left shift Advance Right shift Delay Figure 3.4 time shift

8. 3.2. Useful Signal Operations Signal and System II 8  Time Reversal ,  anchor point : n = 0 cf)  Time Reversal ,  anchor point : n = 0 cf) Figure 3.4 time reversal

9. 3.2. Useful Signal Operations Signal and System II 9  Example 3.2 1. 2.  Example 3.2 1. 2.

10. 3.2. Useful Signal Operations Signal and System II 10  Sampling Rate Alteration : Decimation and Interpolation  decimation ( down sampling ), M must be integer values (3.3)  Sampling Rate Alteration : Decimation and Interpolation  decimation ( down sampling ), M must be integer values (3.3)

11. 3.2. Useful Signal Operations Signal and System II 11  interpolation ( expanding ) L must be integer value more than 2. (3.4)  interpolation ( expanding ) L must be integer value more than 2. (3.4)

12. 3.3. Some Useful DT Signal Models Signal and System II 12 3.3-1 DT Impulse Function (3.5)

13. 3.3. Some Useful DT Signal Models Signal and System II 13 3.3-2 DT Unit Stop Function (3.6)

14. 3.3. Some Useful DT Signal Models Signal and System II 14  Example 3.3 (1) for all  Example 3.3 (1) for all

15. 3.3. Some Useful DT Signal Models Signal and System II 15  Example 3.3 (2)  Example 3.3 (2)

16. 3.3. Some Useful DT Signal Models Signal and System II 16 3.3-3 DT Exponential γ n  CT Exponential ( or ) ex)  ( or )  Nature of  CT Exponential ( or ) ex)  ( or )  Nature of

17. 3.3. Some Useful DT Signal Models Signal and System II 17   plane exp. dec.LHPInside the unit circle exp. inc.RHPOutside the unit circle osc.Imaginary axisUnit circle

18. 3.3. Some Useful DT Signal Models Signal and System II 18

19. 3.3. Some Useful DT Signal Models Signal and System II 19 3.3-4 DT Sinusoid cos(Ωn+Θ)  DT Sinusoid :  : Amplitude  : phase in radians  : angle in radians  : radians per sample  : DT freq. (radians/2π) per sample or cycles for sample, : period (samples/cycle)  DT Sinusoid :  : Amplitude  : phase in radians  : angle in radians  : radians per sample  : DT freq. (radians/2π) per sample or cycles for sample, : period (samples/cycle)

20. 3.3. Some Useful DT Signal Models Signal and System II 20  About Figure 3.10 (cycles/sample) , same freq.  Sampled CT Sinusoid Yields a DT Sinusoid  CT sinusoid  About Figure 3.10 (cycles/sample) , same freq.  Sampled CT Sinusoid Yields a DT Sinusoid  CT sinusoid

21. 3.3. Some Useful DT Signal Models Signal and System II 21 3.3-5 DT Complex Exponential e jΩn freq : a point on a unit circle at an angle of freq : a point on a unit circle at an angle of

22. 3.4. Examples of DT Systems Signal and System II 22 3.4-0  Example 3.4 (Savings Account)  input : a deposit in a bank regularly at an interval T.  output : balance  interest : per dollar per period T. balance y[n] = previous balance y[n-1] + interest on y[n-1] + deposit x[n] or (3.9a) delay operator form (causal)  withdrawal : negative deposit,  loan payment problem : or  (3.9b) advance operator form (noncausal)  Example 3.4 (Savings Account)  input : a deposit in a bank regularly at an interval T.  output : balance  interest : per dollar per period T. balance y[n] = previous balance y[n-1] + interest on y[n-1] + deposit x[n] or (3.9a) delay operator form (causal)  withdrawal : negative deposit,  loan payment problem : or  (3.9b) advance operator form (noncausal)

23. 3.4. Examples of DT Systems Signal and System II 23  Block diagram (a)addition, (b)scalar multiplication, (c)delay, (d)pickoff node  Block diagram (a)addition, (b)scalar multiplication, (c)delay, (d)pickoff node

24. 3.4. Examples of DT Systems Signal and System II 24  Example 3.5 (Scalar Estimate) : th semester : students enrolled in a course requiring a certain textbook : new copies of the book sold in the th semester.  ¼ of students resell the text at the end of the semester.  book life is three semesters. (3.10a) (3.10b)  Block diagram  Example 3.5 (Scalar Estimate) : th semester : students enrolled in a course requiring a certain textbook : new copies of the book sold in the th semester.  ¼ of students resell the text at the end of the semester.  book life is three semesters. (3.10a) (3.10b)  Block diagram (3.10c)

25. 3.4. Examples of DT Systems Signal and System II 25  Example 3.6 (1) (Digital Differentiator) Design a DT system to differentiate CT signals. Signal bandwidth is below 20kHz ( audio system )  Example 3.6 (1) (Digital Differentiator) Design a DT system to differentiate CT signals. Signal bandwidth is below 20kHz ( audio system ) : backward difference

26. 3.4. Examples of DT Systems Signal and System II 26  Example 3.6 (2) : Sufficiently small  Example 3.6 (2) : Sufficiently small

27. 3.4. Examples of DT Systems Signal and System II 27  Example 3.6 (3)  Forward difference  Example 3.6 (3)  Forward difference

28. 3.4. Examples of DT Systems Signal and System II 28  Example 3.7 ( Digital Integrator ) Design a digital integrator as in example 3.6 : accumulator block diagram : similar to that of Figure 3.12 ( )  Example 3.7 ( Digital Integrator ) Design a digital integrator as in example 3.6 : accumulator block diagram : similar to that of Figure 3.12 ( )

29. 3.4. Examples of DT Systems Signal and System II 29  Recursive & Non-recursive Forms of Difference Equation (3.14a), (3.14b)  Kinship of Difference Equations to Differential Equations  Differential eq. can be approximated by a difference eq. of the same order.  The approximation can be made as close to the exact answer as possible by choosing sufficiently small value for.  Order of a Difference Equation  The highest – order difference of the output or input signal, whichever is higher.  Analog, Digital, CT & DT Systems  DT, CT the nature of horizontal axis Analog, Digital the nature of vertical axis. -DT System : Digital Filter -CT System : Analog Filter -C/D, D/C : A/D, D/A  Recursive & Non-recursive Forms of Difference Equation (3.14a), (3.14b)  Kinship of Difference Equations to Differential Equations  Differential eq. can be approximated by a difference eq. of the same order.  The approximation can be made as close to the exact answer as possible by choosing sufficiently small value for.  Order of a Difference Equation  The highest – order difference of the output or input signal, whichever is higher.  Analog, Digital, CT & DT Systems  DT, CT the nature of horizontal axis Analog, Digital the nature of vertical axis. -DT System : Digital Filter -CT System : Analog Filter -C/D, D/C : A/D, D/A

30. 3.4. Examples of DT Systems Signal and System II 30  Advantage of DSP 1.Less sensitive to change in the component parameter values. 2.Do not require any factory adjustment, easily duplicated in volume, single chip (VLSI) 3.Flexible by changing the program 4.A greater variety of filters 5.Easy and inexperience storage without deterioration 6.Extremely low error rates, high fidelity and privacy in coding 7.Serve a number of inputs simultaneously by time-sharing, easier and efficient to multiplex several D. signals on the same channel 8.Reproduction with extreme reliability  Advantage of DSP 1.Less sensitive to change in the component parameter values. 2.Do not require any factory adjustment, easily duplicated in volume, single chip (VLSI) 3.Flexible by changing the program 4.A greater variety of filters 5.Easy and inexperience storage without deterioration 6.Extremely low error rates, high fidelity and privacy in coding 7.Serve a number of inputs simultaneously by time-sharing, easier and efficient to multiplex several D. signals on the same channel 8.Reproduction with extreme reliability  Disadvantage of DSP 1.Increased system complexity (A/D, D/A interface) 2.Limited range of freq. available in practice (about tens of MHz) 3.Power consumption  Disadvantage of DSP 1.Increased system complexity (A/D, D/A interface) 2.Limited range of freq. available in practice (about tens of MHz) 3.Power consumption

31. 3.4. Examples of DT Systems Signal and System II 31 3.4-1 Classification of DT Systems  Linearity & Time Invariance   Systems whose parameters do not change with time (n)  If the input is delayed by K samples, the output is the same as before but delayed by K samples.  Causal & Noncausal Systems  output at any instant depends only on the value of the input for  Invertible & Noninvertible Systems  is invertible if an inverse system exists s.t. the cascade of and results in an identity system Ex) unit delay unit advance ( noncausal ) Cf)  Linearity & Time Invariance   Systems whose parameters do not change with time (n)  If the input is delayed by K samples, the output is the same as before but delayed by K samples.  Causal & Noncausal Systems  output at any instant depends only on the value of the input for  Invertible & Noninvertible Systems  is invertible if an inverse system exists s.t. the cascade of and results in an identity system Ex) unit delay unit advance ( noncausal ) Cf) Ex)for and

32. 3.4. Examples of DT Systems Signal and System II 32  Stable & Unstable Systems (1)  The condition of BIBO ( Boundary Input Boundary Output ) and external stability If is bounded, then, and Clearly the output is bounded if the summation on the right-hand side is bounded; that is  Stable & Unstable Systems (1)  The condition of BIBO ( Boundary Input Boundary Output ) and external stability If is bounded, then, and Clearly the output is bounded if the summation on the right-hand side is bounded; that is

33. 3.4. Examples of DT Systems Signal and System II 33  Stable & Unstable Systems (2)  Internal ( Asymptotic ) Stability For LTID systems, and Since the magnitude of is 1, it is not necessary to be considered. Therefore in case of if as ( stable ) if as ( unstable ) if for all ( unstable )  Stable & Unstable Systems (2)  Internal ( Asymptotic ) Stability For LTID systems, and Since the magnitude of is 1, it is not necessary to be considered. Therefore in case of if as ( stable ) if as ( unstable ) if for all ( unstable )

34. 3.4. Examples of DT Systems Signal and System II 34  Memoryless Systems & Systems with Memory  Memoryless : the response at any instant depends at most on the input at the same instant. Ex)  With memory : depends on the past, present and future values of the input. Ex)  Memoryless Systems & Systems with Memory  Memoryless : the response at any instant depends at most on the input at the same instant. Ex)  With memory : depends on the past, present and future values of the input. Ex)

35. 3.5. DT System Equations Signal and System II 35  Difference Equations (3.16) order :  Causality Condition  causality : if not, would depend on  if, (3.17a)  delay operator form (3.17b)  Difference Equations (3.16) order :  Causality Condition  causality : if not, would depend on  if, (3.17a)  delay operator form (3.17b)

36. 3.5. DT System Equations Signal and System II 36 3.5-1 Recursive (Iterative) Solution of Difference Equations 3.5-1 Recursive (Iterative) Solution of Difference Equations  : initial conditions input for causality  Example 3.8 (1)  : initial conditions input for causality  Example 3.8 (1) (3.17c)

37. 3.5. DT System Equations Signal and System II 37  Example 3.8 (2)

38. 3.5. DT System Equations Signal and System II 38  Example 3.9  Closed – form solution  Example 3.9  Closed – form solution

39. 3.5. DT System Equations Signal and System II 39  Operation Notation  Differential eq. Operator D for differentiation  Difference eq. Operator E for advancing a sequence. (3.24a) (3.24b) (3.24c) (3.24d)  Operation Notation  Differential eq. Operator D for differentiation  Difference eq. Operator E for advancing a sequence. (3.24a) (3.24b) (3.24c) (3.24d)

40. 3.5. DT System Equations Signal and System II 40  Response of Linear DT Systems (3.24a) (3.24b)  LTID system  General solution = ZIR (zero input response) + ZSR (zero state response)  Response of Linear DT Systems (3.24a) (3.24b)  LTID system  General solution = ZIR (zero input response) + ZSR (zero state response)

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