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According to the invariance property of the BCH code and Euclidean algorithm to calculate the greatest common factor (GCF) between code group and its cyclic shift code group. There is a method by using the degree distribution probability sum function of the greatest common factor to recognize the code length of BCH code. On this basis, the GCF can be extracted of the greatest degree distribution probability from the sum function, with the generator polynomial obtained by decomposing the GCF. The simulation results show that this method can achieve the recognition probability above 95% with BER of 4×10-3，and the high BER is much better to recognize the short codes.

The combination of the multi-input and multi-output (MIMO) technology and Orthogonal Frequency Division Multiplexing (OFDM) technology becomes the key technology in 4G mobile telecommunication, which can be against frequency selective fading, increase the data transmission rate and improve the system capacity. The improved RLS algorithm with the adaptive forgetting factor in time-varying MIMO-OFDM system can improve the convergence rate and mean square error (MSE). The improved MIMO-OFDM system applied in the mine communication is a new try to solve the problem of multipath fading and to improve the quality and performance in the mine communication.

For the disadvantage of degrade PAPR property of the existing methods using m sequences in traditional way, which is too simple in the aspects of the conversion from m sequences to rotation factors, an improved algorithm of PTS is proposed. This method can obtained the matrix, depending on the rotation factors including four phases (1,−1,j,-j) by using m sequences, to reserch, so the scope of choice is expanded, and the PAPR of OFDM system is greater reducted. The results of the simulation show that compared to the methods using m sequences in traditional way, the modified method basically doesn't increase the complexity of the system, while PAPR has been in a situation of better control.

The paper presents a new algorithm of digital modulation signals based on high order cumulants (HOC) and support vector machines (SVM). The parameters which are picked up from the signals' fourth order and sixth order cumulants are used as the classification feature vectors. Using SVM based on binary tree as classifiers, recognition of the 2ASK, 4ASK, QPSK, 2FSK and 4FSK signals is efficient. The computer simulation results justify that the success rate is over 97.5% at SNR=10 dB.

This paper proposes a union algorithm of SLM and PTS to reduce PAPR in OFDM system. The simulation results show that the union algorithm can better reduce the complexity of OFDM than traditional SLM or PTS algorithm, and equally effective in restraining the growth of the PAPR.

A new algorithm based on high order cumulants(HOC) and support vector machines(SVM) for modulation and recognition of digital communication signals is proposed. The new method can identify six digital modulation signals: 2ASK, 4ASK, 8ASK, 4PSK, 8PSK and 16QAM digital signals using fourth and sixth order cumulants of the signals as vectors and SVM based on binary tree as classifiers. The method uses new class distance as rules of constructing binary tree, which separates the furthest class from others first, so that the method can maintain high generalization ability. The computer simulation results justify the method's validity.

According to mathematic statistics, data for laser microemission spectroscopic analysis were selected, which were collected with the use of CCD (charge-coupled device) in arg on atmosphere at reduced pressure. By selection, the effects of some factors, such as the difference of bore ablated on the sample surface by the laser, the distribution nonuniformity of element in the sample, and the fluctuation of output energy of the laser, etc. were reduced. The method that improves analytic precision of laser microemission spectroscopic analysis was studied. And quantitative analysis of Cu, Zn and Mg in aluminum alloy standard samples was performed, using the Cu (I) line at 324.7 nm, the Zn (I) line at 334.5 nm, and the Mg (I) line at 383.8 nm. The results show that the RSDs of relative intensity of the spectral lines of Cu, Zn, Mg are 1.80%, 4.35% and 6.29% respectively, and the RSDs of quantitative analysis of them are 10.1%, 6.98% and 8.17% respectively. The relative errors of the average of analysis of them are -3.76%, 3.62% and -1.62% respectively.