The Research and Application of Auto-Focus Based on Hi3515

2012 ◽  
Vol 192 ◽  
pp. 440-444
Author(s):  
Yan Long Liu ◽  
Jian Jun Guo ◽  
Fu Mei Zhao
Keyword(s):  
Fourier Transform ◽  
Wavelet Transform ◽  
High Speed ◽  
The Other ◽  
Hill Climbing ◽  
Discrete Wavelet ◽  
Key Technology ◽  
Integer Dct ◽  
Auto Focus ◽  
Peak Value

Auto-focus is a key technology for visual presenter, this paper mainly presents how to achieve the function of auto-focus on Hi3515. The 4x4 integer DCT (Discrete Cosine Transform) shown as Eq. (2) was used to indicate whether the system was on accurate focus or not. Because the 4x4 integer DCT not only has the characteristics of single peak value, non-deflection, reliability, high-speed, but also has lower complex computation than the other frequency methods such as FFT(Fast Fourier Transform), DWT (Discrete Wavelet Transform). This paper employed the method of monotonic and blind hill climbing to achieve auto-focus. The result of auto-focus is shown as Fig. 6.

The Study of Tire Pattern Noise by Using Wavelet Transform

2011 ◽  
Vol 105-107 ◽  
pp. 267-270 ◽  
Author(s):  
Sung Wook Hwang ◽  
Jin Hyuk Han ◽  
Ki Duck Sung ◽  
Sang Kwon Lee
Keyword(s):  
Fourier Transform ◽  
Wavelet Transform ◽  
The Other ◽  
Road Noise ◽  
Signal Process ◽  
The Road ◽  
Pattern Noise ◽  
On The Road ◽  
Non Stationary Signal ◽  
The Relationship

Tire noise is classified by pattern noise and road noise in a vehicle. Especially pattern noise has impulsive characteristics since it is generated by impacting of tire’s block on the road. Therefore, a special signal process is needed other than traditional Fourier Transform, because the characteristic of signal is varying with time. On the other hand, the pattern noise is a kind of non-stationary signal and is related to the impulsive train of pitch sequence of a block. In this paper, Wavelet Transform is applied to verify the impulse signal caused by impact of block and groove and to verify the relationship between the pattern noise and the train of pitch sequence.

BER Improvement in OFDM Systems Using Wavelet Transform Based on Kalman Filter

2020 ◽  
pp. 102-124
Author(s):  
Sajjan Singh
Keyword(s):  
Kalman Filter ◽  
Wavelet Transform ◽  
Fading Channels ◽  
Communication Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
High Speed ◽  
Performance Enhancement ◽  
Average Power ◽  
Discrete Wavelet ◽  
Rate Analysis

Orthogonal frequency division multiplexing (OFDM) is an efficient method of data transmission for high speed communication systems over multipath fading channels. However, the peak-to-average power ratio (PAPR) is a major drawback of multicarrier transmission systems such as OFDM is the high sensitivity of frequency offset. The bit error rate analysis (BER) of discrete wavelet transform (DWT)-OFDM system is compared with conventional fast Fourier transform (FFT)-OFDMA system in order to ensure that wavelet transform based OFDMA transmission gives better improvement to combat ICI than FFT-based OFDMA transmission and hence improvement in BER. Wavelet transform is applied together with OFDM technology in order to improve performance enhancement. In the proposed system, a Kalman filter has been used in order to improve BER by minimizing the effect of ICI and noise. The obtained results from the proposed system simulation showed acceptable BER performance at standard SNR.

Phase-based spectrum analysis method for identifying weak harmonics

2018 ◽  
Vol 24 (23) ◽  
pp. 5585-5596 ◽  
Author(s):  
Jingsong Xie ◽  
Wei Cheng ◽  
Yanyang Zi ◽  
Mingquan Zhang
Keyword(s):  
Signal Processing ◽  
Fourier Transform ◽  
Wavelet Transform ◽  
Characteristic Frequency ◽  
Discrete Wavelet ◽  
Accurate Identification ◽  
Processing Methods ◽  
Characteristic Frequencies ◽  
Frequency Detection ◽  
Signal Processing Methods

Fault characteristic frequency extraction is an important means for the fault diagnosis of rotating machineries. Traditional signal processing methods commonly use the amplitude information of signals to detect damages. However, when the amplitudes of characteristic frequencies are weak, the recognition effects of traditional methods may be unsatisfactory. Therefore, this paper proposes the phase-based enhanced phase waterfall plot (EPWP) method and frequency equal ratio line (FERL) method for identifying weak harmonics. Taking a cracked rotor as an example, the characteristic frequency detection performances of the EPWP and FERL methods are compared with that of the traditional signal processing methods namely fast Fourier transform, short-time Fourier transform, discrete wavelet transform, continuous wavelet transform, ensemble empirical mode decomposition, and Hilbert–Huang transform. Research results demonstrate that the effects of EPWP and FERL for the recognitions of weak harmonics which are contained in steady signals and transient signals are better than that of the traditional signal processing methods. The accurate identification of weak characteristic frequencies in the vibration signals can provide an important reference for damage detections and improve the diagnostic accuracy.

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