>> a = [0 40 80 120 160 200 220 255];
>> b = [a;a;a;a;a;a;a;a];
>> colormap('gray');
>> imagesc(b)
Result:
Information about Electrical, Electronic, Communication and Computer Engineering 電機、電子、通訊、電腦資訊工程的學習筆記
相關資訊~生醫工程:StudyBME
聽力科技相關資訊:電子耳資訊小站
iOS程式語言:Study Swift
樹莓派和Python:Study Raspberry Pi
2017/04/06
2017/04/03
Modulation terms 調變相關名詞
modulation 調變
modulator 調變器
demodulator 解調器/解調變器
amplitude modulation (AM) 振幅調變/調幅
angle modulation 角度調變
- frequency modulation (FM) 頻率調變/調頻
- phase modulation (PM) 相位調變/調相
modulation index 調變指數
Reference
S. Haykin, Communication Systems, 4th Edition, Wiley, pp106
國家教育研究院雙語詞彙、學術名詞暨辭書資訊網
modulator 調變器
demodulator 解調器/解調變器
amplitude modulation (AM) 振幅調變/調幅
angle modulation 角度調變
- frequency modulation (FM) 頻率調變/調頻
- phase modulation (PM) 相位調變/調相
modulation index 調變指數
Reference
S. Haykin, Communication Systems, 4th Edition, Wiley, pp106
國家教育研究院雙語詞彙、學術名詞暨辭書資訊網
2017/03/18
樂器的ADSR模型
A sound produced by a musical instrument can be explained using the ADSR model, which involves 4 stages:
attack
decay
sustain
release
attack
decay
sustain
release
2017/03/13
Matlab: Length and Size of a Vector/Matrix
Given that
>> a = [1 2 3;4 5 6]
>> b = 1:5
Length
>> length(a)
ans =
3
>> length(b)
ans =
5
Size
>> size(a)
ans =
2 3
>> size(b)
ans =
1 5
>> a = [1 2 3;4 5 6]
>> b = 1:5
>> length(a)
ans =
3
>> length(b)
ans =
5
Size
>> size(a)
ans =
2 3
>> size(b)
ans =
1 5
Matlab: How to use Quantiz with partition and codebook
The Quantiz function requires the Communications System Toolbox.
This quantization function requires at least an input signal and a partition vector.
Partition
The example below shows an input signal between 1 and 10. The partition vector equals [2 5 7]. When the signal is quantized, values become:
y = 0 if x <= 2
y = 1 if x <= 5
y = 2 if x <= 7
y = 3 if x > 7
>> x = 1:10
x =
1 2 3 4 5 6 7 8 9 10
>> partition = [2 5 7]
partition =
2 5 7
>> y = quantiz(x, partition)
y =
0 0 1 1 1 2 2 3 3 3
Codebook
Using the same input signal x and partition above, add a codebook as:
>> codebook = [-4 0 2 4]
Insert the codebook as the third parameter in the Quantiz function. The index and quantized value quants are output:
>> [index,quants] = quantiz(x,partition,codebook)
index =
0 0 1 1 1 2 2 3 3 3
quants =
-4 -4 0 0 0 2 2 4 4 4
Reference
Quantization (MathWorks)
This quantization function requires at least an input signal and a partition vector.
Partition
The example below shows an input signal between 1 and 10. The partition vector equals [2 5 7]. When the signal is quantized, values become:
y = 0 if x <= 2
y = 1 if x <= 5
y = 2 if x <= 7
y = 3 if x > 7
>> x = 1:10
x =
1 2 3 4 5 6 7 8 9 10
>> partition = [2 5 7]
partition =
2 5 7
>> y = quantiz(x, partition)
y =
0 0 1 1 1 2 2 3 3 3
Codebook
Using the same input signal x and partition above, add a codebook as:
>> codebook = [-4 0 2 4]
Insert the codebook as the third parameter in the Quantiz function. The index and quantized value quants are output:
>> [index,quants] = quantiz(x,partition,codebook)
index =
0 0 1 1 1 2 2 3 3 3
quants =
-4 -4 0 0 0 2 2 4 4 4
Reference
Quantization (MathWorks)
2017/03/12
PCM, DPCM, ADPCM
2017/02/13
Sampling 取樣
Discrete-time signal x[n] is obtained by sampling a continuous-time signal xc(t):
x[n] = xc(nT) , -∞ < n < ∞
Fourier Transform:
xc(t) <--F--> X(jΩ)
x[n] <--F--> X(ejω)
ω = ΩT
Time Shift:
x(t-t0) <--F--> e-jΩt0 X(jΩ)
x[n-n0] <--F--> e-jωn0 X(ejω)
Frequency Shift:
ejΩ0t x(t) <--F--> X(j(Ω-Ω0))
ejω0n x[n] <--F--> X(ej(ω-ω0))
sampling period 取樣周期 T
sampling frequency 取樣頻率 fs or Ωs
With respect to different units:
Samples/second: fs = 1/T
Radians/second: Ωs = 2π/T = 2πfs
Nyquist Theorem
Nyquist Frequency ΩN
Nyquist Rate 2ΩN
aliasing 頻疊、摺疊效應
To avoid aliasing, Ωs >= 2ΩN
Foldover 反摺、混疊
- when the sampling rate is too low
Reference
Discrete-Time Signal Processing (2nd edition), A. Oppenheim & R. Schafer:
Fourier transform and inverse Fourier transform - p28
Time shift & frequency shift - Table 2.2, p59
Proof for time shift in z-transform - 3.4.2, p120
x[n] = xc(nT) , -∞ < n < ∞
Fourier Transform:
xc(t) <--F--> X(jΩ)
x[n] <--F--> X(ejω)
ω = ΩT
Time Shift:
x(t-t0) <--F--> e-jΩt0 X(jΩ)
x[n-n0] <--F--> e-jωn0 X(ejω)
Frequency Shift:
ejΩ0t x(t) <--F--> X(j(Ω-Ω0))
ejω0n x[n] <--F--> X(ej(ω-ω0))
sampling period 取樣周期 T
sampling frequency 取樣頻率 fs or Ωs
With respect to different units:
Samples/second: fs = 1/T
Radians/second: Ωs = 2π/T = 2πfs
Nyquist Theorem
Nyquist Frequency ΩN
Nyquist Rate 2ΩN
aliasing 頻疊、摺疊效應
To avoid aliasing, Ωs >= 2ΩN
Foldover 反摺、混疊
- when the sampling rate is too low
Reference
Discrete-Time Signal Processing (2nd edition), A. Oppenheim & R. Schafer:
Fourier transform and inverse Fourier transform - p28
Time shift & frequency shift - Table 2.2, p59
Proof for time shift in z-transform - 3.4.2, p120
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