台北科技大學資訊工程系實務專題計畫成果報告超級麥克風專題編號：093CSIE-S009 專題計劃參與人員：92590012 曾智鵬 92590030 賴柏林指導教授：尤信程副教授執行期間：92 年 2 學期至 93 年 1 學期

台北科技大學資訊工程系 - 歡迎蒞臨國立 ...csie.ntut.edu.tw/labaspl/chinese/presentation/super_mic.pdf · 了。所以數位訊號處理的知識也就愈來愈重要。

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093CSIE-S009

92590012

92590030

92 2 93 1
i

.................................................. 1 1.1 ............................................... 1 DSP .............................................. 3 2.1 DSP(Digital Signal Processor) ........................... 3 2.2 ................................. 3 2.3 ........................................... 5 2.4 ............................................. 6 Adaptive filter .............................. 8 3.1 Adaptive filter ............................. 8 3.2 .............................................. 10 ................................................. 12 4.1 ................................................ 12 4.2 ................................................ 12 4.3 .................................................... 14 ................................................ 23 24
1

1.1
2

DSP Adaptive Filter LMS
3

DSP

2.1 DSP(Digital Signal Processor)

SOC (System On Chip)

(IC design)

IC design SOC IC

design (

) Sensor (MEMS)

IC design MEMS

(Portable)

(DSP) DSP

DSP (pipeline)DSP

2.2

DSP

DSP

(1)

(programmable)

12

DSP 12

DSP
4

(2)

0.1%

A/D

(3)

(DSP)

(1)

DSP

DSP

(2)

(Digital)

CPU

DSP

(3)

(4)

(1)
5

(2)

(3) 80X86

8051PICZ80

(1)

(2)

(3)

2.3

1 DSP
6

1 DSP

2.4

(sample)

...

FIR

FIR

IIR

IIR IIR
7

DSPs

DSP

1 AV DTSDolby AC-3Pro LogicMPEG2

2 MODEM

3

4 UPS

5

6

7

8 CAD/CAM

9

10 ABS

1 DSP
8

Adaptive filter

3.1 Adaptive filter

(A) DSP

Signal+Noise(B)

Signal

180

(Adaptive Noise Canceller)

(Adaptive filter) n1 y = n0

Output = e = d(n) y(n)

(Adaptive filter)

e

Noise FIR digital filter

Adaptive filterW(n)

y(n)

e(n)

d(n)Signal+Noise

x(n)

3.1
9

(non-stationary) Adaptive filter (gradient based algorithm)(steepest-descentmethod)()(local)

m(step-size)m

d(n)=signal + noise x(n)=noise e(n)=d(n)-y(n)

d(n)x(n)

Widrow

(instantaneous square error) ) (

(least mean square ,LMS)
10

3.2

Delay-and-Sum Beamformer (Johnsonand Dudgeon, 1993)

i i+1 d

i t

i i+1 R (R= cos d )3.2

3.2

C(cm/sec)i i+1

i i+1

Delay-and-Sum Beamformer 3.3

3.3Delay-and-Sum Beamformer
11

Delay-and-Sum Beamformer

M
12

5.1

1. 2. 3.(Debug) 4. 5.

5.2

1. PC 2.

3.

4.

5. TMS320VC5416

TMS320VC5416 DSP(DSK)TMS320VC5416 DSP

TMS320C54X DSP

(plug-and-play)USB

DSP

VC5416 DSKRTDX

TMS320VC5416 DSK

/

TMS320VC5416DSKTMS320VC5416DSPDSPVC5416DSP

160MIPS128K16DSK

* USBJTAG
13

* 16/20bitA/DD/A(Codec)

* 3.5mmline in , line out

* 256K 16Flash64K 16SRAM

* TITIEVM

* JTAGDSP

* +5V

6. Cool Edit
14

5.3

1k HZ 100mv

4.3.1 1k HZ 100 mv 1 10

4.1

4.2
15

4.3 Adaptive filter

4.4 Adaptive filter
16

4.5

4.6
17

4.3.2 1 10

4.7

4.8
18

4.9 Adaptive filter

4.10 Adaptive filter
19

4.11

4.12
20

4.3.3 1 10

4.13

4.14
21

4.15 Adaptive filter

4.16 Adaptive filter
22

4.17

4.17
23

5.1

1. Adaptive filter

Adaptive filter

,

!

2.

!

5.2

RLSFTF(Fast Transversal Filter)
24

: