The paper presents a parallel ATPG algorithm - PTGBP, which aims at decreasing the complexity of the ATPG by partitioning circuit under test (CUT) to big function blocks (BFB) and processing them parallelly. PTGBP ado...The paper presents a parallel ATPG algorithm - PTGBP, which aims at decreasing the complexity of the ATPG by partitioning circuit under test (CUT) to big function blocks (BFB) and processing them parallelly. PTGBP adopts hybrid circuit mode and hybrid fault model, and organizes the parallel course in term of master/slave mode. Master processor loads the whole netlist of CUT based on BFB, every slave processor loads logic level (gate/function block/basic logic units) netlist of a BFB. Test generation (TG) uses BFB input/output s-a-0/s-a-1 fault model; fault simulation uses logic level single stuck fault model. Master controls the PTGBP’s running course and ensures the correctness of its running result; slaves provide the results of fault sensitization compatible computation and fault simulation to master parallelly. PTGBP algorithm is under implementation.展开更多
For the direction of arrival（DOA） estimation,traditional sparse reconstruction methods for wideband signals usually need many iteration times.For this problem,a new method for two-dimensional wideband signals based ...For the direction of arrival（DOA） estimation,traditional sparse reconstruction methods for wideband signals usually need many iteration times.For this problem,a new method for two-dimensional wideband signals based on block sparse reconstruction is proposed.First,a prolate spheroidal wave function（PSWF） is used to fit the wideband signals,then the block sparse reconstruction technology is employed for DOA estimation.The proposed method uses orthogonalization to choose the matching atoms,ensuring that the residual components correspond to the minimum absolute value.Meanwhile,the vectors obtained by iteration are back-disposed according to the corresponding atomic matching rules,so the extra atoms are abandoned in the course of iteration,and the residual components of current iteration are reduced.Thus the original sparse signals are reconstructed.The proposed method reduces iteration times comparing with the traditional reconstruction methods,and the estimation precision is better than the classical two-sided correlation transformation（TCT）algorithm when the snapshot is small or the signal-to-noise ratio（SNR） is low.展开更多
基金Supported by National Natural Science Founding of China.
文摘The paper presents a parallel ATPG algorithm - PTGBP, which aims at decreasing the complexity of the ATPG by partitioning circuit under test (CUT) to big function blocks (BFB) and processing them parallelly. PTGBP adopts hybrid circuit mode and hybrid fault model, and organizes the parallel course in term of master/slave mode. Master processor loads the whole netlist of CUT based on BFB, every slave processor loads logic level (gate/function block/basic logic units) netlist of a BFB. Test generation (TG) uses BFB input/output s-a-0/s-a-1 fault model; fault simulation uses logic level single stuck fault model. Master controls the PTGBP’s running course and ensures the correctness of its running result; slaves provide the results of fault sensitization compatible computation and fault simulation to master parallelly. PTGBP algorithm is under implementation.
基金supported by the National Natural Science Foundation of China(6150117661201399)+1 种基金the Education Department of Heilongjiang Province Science and Technology Research Projects(12541638)the Developing Key Laboratory of Sensing Technology and Systems in Cold Region of Heilongjiang Province and Ministry of Education,(Heilongjiang University),P.R.China(P201408)
文摘For the direction of arrival（DOA） estimation,traditional sparse reconstruction methods for wideband signals usually need many iteration times.For this problem,a new method for two-dimensional wideband signals based on block sparse reconstruction is proposed.First,a prolate spheroidal wave function（PSWF） is used to fit the wideband signals,then the block sparse reconstruction technology is employed for DOA estimation.The proposed method uses orthogonalization to choose the matching atoms,ensuring that the residual components correspond to the minimum absolute value.Meanwhile,the vectors obtained by iteration are back-disposed according to the corresponding atomic matching rules,so the extra atoms are abandoned in the course of iteration,and the residual components of current iteration are reduced.Thus the original sparse signals are reconstructed.The proposed method reduces iteration times comparing with the traditional reconstruction methods,and the estimation precision is better than the classical two-sided correlation transformation（TCT）algorithm when the snapshot is small or the signal-to-noise ratio（SNR） is low.
