Extraction of intrinsic response from S-parameters of laser diodes

We describe a new method for extracting the intrinsic response of a laser diode from S-parameters measured using a calibrated vector network analyzer. The experimental results obtained using the new method are compared with those obtained using the optical modulation method and the frequency response subtraction method. Good agreement has been obtained, confirming the new method validity and accuracy. The new method has the advantages of obtaining the intrinsic characteristics of a laser diode with conventional measurements using a network analyzer.

Wavelet denoising and feature extraction of seismic signal for footstep detection

Seismic sensors are widely used to detect moving target in ground sensor networks. Footstep detection is very important for security surveillance and other applications. Because of non-stationary characteristic of seismic signal and complex environment conditions, footstep detection is a very challenging problem. A novel wavelet denoising method based on singular value decomposition is used to solve these problems. The signal-to-noise ratio (SNR) of raw footstep signal is greatly improved using this strategy. The feature extraction method is also discussed after denosing procedure. Comparing, with kurtosis statistic feature, the wavelet energy feature is more promising for seismic footstep detection, especially in a long distance surveillance.

Design of slow extraction system for therapy synchrotron

Based on the optimized design of the lattice for therapy synchrotron and considering the requirement of radiation therapy, the third order resonant extraction is adopted. Using the momentum-amplitude selection method, the extraction system is designed and optimized. An extraction efficiency of more than 97% and a momentum spread less than 0.11% are obtained.