Principle And Algorithm Of Analog Information Converter

Digital technology has become a medium of interaction between human and society,but most of the information in nature does not exist in a digital way.Transforming analog signals into digital signals is the most critical step in the information processing process.The analog-digital converter(ADC)based on the traditional Nyquist sampling theory has strict requirements on sampling frequency,and it is more and more difficult to meet the sampling processing of ultra bandwidth and high frequency signals.In order to realize low-speed sampling and relieve the pressure of data transmission,storage and processing,analog to information converter(AIC)based on Nyquist sampling has come into people's vision.In this paper,based on the theory of compressed sensing,the signal is sampled by Nyquist,and the reconstruction algorithm is used to recover the signal and analyze the error of the recovered signal.Because the greedy algorithm which is solved by linear underdetermined equation is used to recover the signal,sometimes it may cause the loss of the important signal.In order to complete the accurate transmission of the signal,the fault tolerance design of the recovered signal is carried out to ensure the integrity of the signal transmitted to the back end.The main contents of this paper are as follows:First,it combs the analog information converter and the traditional analog-to-digital converter,analyzes the basic principles of the two converters,and compares the advantages and disadvantages.Due to the development of electronic technology,in response to some ultra bandwidth signals,the traditional analog-to-digital converter is more and more difficult to meet the requirements of the sampling frequency.In order to realize the Nyquist sampling of the signal,the compressed sensing theory has been developed.The compressed sensing theory has been elaborated in detail,and its time line has been regulated to complete the supplement of its theoretical knowledge.Secondly,the three hot topics of compressed sensing theory are mainly the exploration of sparsity in the physical world of signal,the construction of signal measurement matrix and the reconstruction algorithm of original signal recovery.In the design of analog information converter,the feasibility of theory and practice should be considered comprehensively,so as to choose a suitable framework to realize.In this paper,after comparing several classical implementation structures,we choose the structure of modulation bandwidth converter to carry out theoretical experiments,and use matlab to verify the theoretical feasibility of the structure according to the structural principle block diagram of modulation bandwidth converter Sex.Finally,it is the most important step to recover the original signal by using the compressed perceptual reconstruction algorithm.In this paper,an improved algorithm based on the generalized orthogonal matching tracking algorithm is proposed,aiming at the situation of selecting inaccurate atoms when selecting the atom iteration in the generalized orthogonal matching tracking algorithm.The algorithm uses the inner product method to find the best matching atomic index in the cycle process and does not have the corresponding strategy to delete too many wrong atoms when adding the best matching atomic index to the estimation support set in the iteration process.