human information processing ii

27
Digital Media Lab Umeå University Computational Perception Human Information Processing II Haibo Li

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Page 1: Human Information Processing II

Digital Media LabUmeå University

Computational Perception

Human Information Processing II

Haibo Li

Page 2: Human Information Processing II

Digital Media LabUmeå University

ComputingSignal Analysis

Page 3: Human Information Processing II

Digital Media LabUmeå University

A Typic Signal

Time

Pres

sure

One cycle

Frequency = number of cycles per second

unit of frequency: Hertz (Hz)

e.g. 400 Hz = 400 cycles per second

Page 4: Human Information Processing II

Digital Media LabUmeå University

How to Characterize a Signal?

Page 5: Human Information Processing II

Digital Media LabUmeå University

Fourier Told Us.........

Page 6: Human Information Processing II

Digital Media LabUmeå University

Fourier Transform

Pres

sure

TimeFreq

Pres

sure

Pres

sure

TimeFreq

Pres

sure

SSinewaveinewavepitch ~ frequency

unidimensional (low to high)

range of hearing: 20 Hz – 20000 Hz

Page 7: Human Information Processing II

Digital Media LabUmeå University

Consider the situation in which we have two tones of different frequencies presented simultaneously.

+ =

Signal Synthesis

Page 8: Human Information Processing II

Digital Media LabUmeå University

A preliminary analysis of a sound mixture into individual frequency components

.

.

.

Signal Analysis

Page 9: Human Information Processing II

Digital Media LabUmeå University

Fourier Transform

Pres

sure

Time

Freq

Pres

sure

f 2f

f 3f 5f 7f 9f

1/31/5 1/7 1/9

Page 10: Human Information Processing II

Digital Media LabUmeå University

400

Leve

l (dB

)

2400. . . 400Le

vel (

dB)

2400. . .

Signal Characterization

Page 11: Human Information Processing II

Digital Media LabUmeå University

Natural Signals

Spatial frequency

Rel

ativ

e am

plitu

de

Page 12: Human Information Processing II

Digital Media LabUmeå University

Human Information Processing

Page 13: Human Information Processing II

Digital Media LabUmeå University

Signal Transmission

Channelx(t) y(t)

X(f) H(f) Y(f)

Y(f)=X(f)H(f)

H(f)

Page 14: Human Information Processing II

Digital Media LabUmeå University

Channel=”Bandpass Filter”

Page 15: Human Information Processing II

Digital Media LabUmeå University

Effect of degrading the speech signal by spectral filtering

The original speech signal contains significant energy up to 7 kHz

a) signal bandpass filtered (0.25 - 0.75 kHz)

b) signal bandpass filtered (1.0 – 3.0 kHz)

c) original signal

Effect of Bandpass

Page 16: Human Information Processing II

Digital Media LabUmeå University

Brain Wave

Page 17: Human Information Processing II

Digital Media LabUmeå University

Bandpass System

Most long-haul transmission systems have a bandpassFrequency response

The transfer function can be written as

)(11)(

ffo

fofjQ

fH−+

=

where the resonant frequency fo and quality factor Q are

LCof

π21= L

CRQ =

Qfo

lu ffB =−=

The 3dB bandwidth between the lower and upper cutoff

frequencies is

=

R

L C

B

fl fo fu

f

1.00.707

Page 18: Human Information Processing II

Digital Media LabUmeå University

Bandpass SystemSince practical tuned circuits usually have 10 < Q <100,the fractional bandwidth B/fc should be kept within the range

1.001.0 <<cf

B

As a rough rue of thumb, the carrier frequencies and corresponding nominal bandwidth can be

cfB 02.0≈

Page 19: Human Information Processing II

Digital Media LabUmeå University

Bandpass System

1013 Hz5x1014 HzOptical2 GHz1 00 GHzMillimeterwave

100 MHz5 GHzMicrowave2 MHz100 MHzVHF

100 kHz5 MHzShortwave radio2 kHz100 kHzLongwave radio

BandwidthCarrier frequency

Frequency band

Selected carrier frequencies and nominal bandwidth

Page 20: Human Information Processing II

Digital Media LabUmeå University

How to Transmit Natural Signals

M

Page 21: Human Information Processing II

Digital Media LabUmeå University

Modulation

Page 22: Human Information Processing II

Digital Media LabUmeå University

Modems and Modem Standards

Page 23: Human Information Processing II

Digital Media LabUmeå University

Nyquist Sampling Rate

t

S(t)

f

S(f)

w

Page 24: Human Information Processing II

Digital Media LabUmeå University

Nyquist Sampling Rate

t

S(t)

f

S(f)

w

Error-free reconstruction when

fs >=2W

Signal Analysis

Page 25: Human Information Processing II

Digital Media LabUmeå University

Quantization

R= - 1/2 log2 D bits/sample

Page 26: Human Information Processing II

Digital Media LabUmeå University

Digital Encoding of Analog Data

Page 27: Human Information Processing II

Digital Media LabUmeå University