Binary Code Similarity Detection(BCSD)is vital for vulnerability discovery,malware detection,and software security,especially when source code is unavailable.Yet,it faces challenges from semantic loss,recompilation va...Binary Code Similarity Detection(BCSD)is vital for vulnerability discovery,malware detection,and software security,especially when source code is unavailable.Yet,it faces challenges from semantic loss,recompilation variations,and obfuscation.Recent advances in artificial intelligence—particularly natural language processing(NLP),graph representation learning(GRL),and large language models(LLMs)—have markedly improved accuracy,enabling better recognition of code variants and deeper semantic understanding.This paper presents a comprehensive review of 82 studies published between 1975 and 2025,systematically tracing the historical evolution of BCSD and analyzing the progressive incorporation of artificial intelligence(AI)techniques.Particular emphasis is placed on the role of LLMs,which have recently emerged as transformative tools in advancing semantic representation and enhancing detection performance.The review is organized around five central research questions:(1)the chronological development and milestones of BCSD;(2)the construction of AI-driven technical roadmaps that chart methodological transitions;(3)the design and implementation of general analytical workflows for binary code analysis;(4)the applicability,strengths,and limitations of LLMs in capturing semantic and structural features of binary code;and(5)the persistent challenges and promising directions for future investigation.By synthesizing insights across these dimensions,the study demonstrates how LLMs reshape the landscape of binary code analysis,offering unprecedented opportunities to improve accuracy,scalability,and adaptability in real-world scenarios.This review not only bridges a critical gap in the existing literature but also provides a forward-looking perspective,serving as a valuable reference for researchers and practitioners aiming to advance AI-powered BCSD methodologies and applications.展开更多
Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Althoug...Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Although adversarial examples can strategically undermine the accuracy of BCSD models and protect critical code,existing techniques predominantly depend on inserting artificial instructions,which incur high computational costs and offer limited diversity of perturbations.To address these limitations,we propose AIMA,a novel gradient-guided assembly instruction relocation method.Our method decouples the detection model into tokenization,embedding,and encoding layers to enable efficient gradient computation.Since token IDs of instructions are discrete and nondifferentiable,we compute gradients in the continuous embedding space to evaluate the influence of each token.The most critical tokens are identified by calculating the L2 norm of their embedding gradients.We then establish a mapping between instructions and their corresponding tokens to aggregate token-level importance into instructionlevel significance.To maximize adversarial impact,a sliding window algorithm selects the most influential contiguous segments for relocation,ensuring optimal perturbation with minimal length.This approach efficiently locates critical code regions without expensive search operations.The selected segments are relocated outside their original function boundaries via a jump mechanism,which preserves runtime control flow and functionality while introducing“deletion”effects in the static instruction sequence.Extensive experiments show that AIMA reduces similarity scores by up to 35.8%in state-of-the-art BCSD models.When incorporated into training data,it also enhances model robustness,achieving a 5.9%improvement in AUROC.展开更多
A decoding algorithm based on revised syndromes to decode the binary (23,12,7) Golay code is presented. The algorithm strongly depends on the algebraic properties of the code. For the algorithm, the worst complexity i...A decoding algorithm based on revised syndromes to decode the binary (23,12,7) Golay code is presented. The algorithm strongly depends on the algebraic properties of the code. For the algorithm, the worst complexity is about 683 mod2 additions, which is less than that of the algorithms available for the code, the average complexity is approximately 319 mod2 additions, which is slightly more than that of Blaum’s algorithm for the code.展开更多
In 5G new radio(NR), polar codes are adopted for e MBB downlink control channels where the blind detection is employed in user equipment(UE) to identify the correct downlink control information(DCI). However, differen...In 5G new radio(NR), polar codes are adopted for e MBB downlink control channels where the blind detection is employed in user equipment(UE) to identify the correct downlink control information(DCI). However, different from that in the 4G LTE system, the cyclic redundancy check(CRC) in polar decoding plays both error correction and error detection roles. Consequently, the false alarm rates(FAR) may not meet the system requirements(FAR<1.52 × 10^(−5)). In this paper, to mitigate the FAR in polar code blind detection, we attach a binary classifier after the polar decoder to further remove the false alarm results and meanwhile retain the correct DCI. This classifier works by tracking the squared Euclidean distance ratio(SEDR) between the received signal and hypothesis. We derive an analytical method to fast compute proper classification threshold that is implementation-friendly in practical use. Combining the well-designed classifier, we show that some very short CRC sequences can even be used to meet the FAR requirements. This consequently reduces the CRC overhead and contributes to the system error performance improvements.展开更多
A new non-binary decoding method, which is called Yaletharatalhussein decoding algorithm, is designed and implemented for decoding non-binary convolutional codes which is based on the trellis diagram representing the ...A new non-binary decoding method, which is called Yaletharatalhussein decoding algorithm, is designed and implemented for decoding non-binary convolutional codes which is based on the trellis diagram representing the convolutional encoder. Yaletharatalhussein decoding algorithm outperforms the Viterbi algorithm and other algorithms in its simplicity, very small computational complexity, decoding reliability for high states TCM codes that suitable for Fourth-Generation (4G), decreasing errors with increasing word length, and easy to implement with real-time applications. The proposed Yaletharatalhussein decoding algorithm deals with non-binary error control coding of the convolutional and TCM codes. Convolutional codes differ from block codes in that a block code takes a fixed message length and encodes it, whereas a convolutional code can encode a continuous stream of data, and a hard-decision decoding can easily be realized using the Yaletharatalhussein algorithm. The idea of non-binary codes has been extended for symbols defined over rings of integers, which outperform binary codes with only a small increase in decoding complexity. The simulation results show that the performance of the nonbinary TCM-based Yaletharatalhussein algorithm outperforms the binary and non-binary decoding methods.展开更多
In this paper, a statistical recognition method of the binary BCH code is proposed. The method is applied to both primitive and non-primitive binary BCH code. The block length is first recognized based on the cyclic f...In this paper, a statistical recognition method of the binary BCH code is proposed. The method is applied to both primitive and non-primitive binary BCH code. The block length is first recognized based on the cyclic feature under the condition of the frame length known. And then candidate polynomials are achieved which meet the restrictions. Among the candidate polynomials, the most optimal polynomial is selected based on the minimum rule of the weights sum of the syndromes. Finally, the best polynomial was factorized to get the generator polynomial recognized. Simulation results show that the method has strong capability of anti-random bit error. Besides, the algorithm proposed is very simple, so it is very practical for hardware im-plementation.展开更多
The m series with 511 bits is taken as an example being applied in non-coherent integra- tion algorithm. A method to choose the bi-phase code is presented, which is 15 kinds of codes are picked out of 511 kinds of m s...The m series with 511 bits is taken as an example being applied in non-coherent integra- tion algorithm. A method to choose the bi-phase code is presented, which is 15 kinds of codes are picked out of 511 kinds of m series to do non-coherent integration. It is indicated that the power in- creasing times of larger target sidelobe is less than the power increasing times of smaller target main- lobe because of the larger target＇ s pseudo-randomness. Smaller target is integrated from larger tar- get sidelobe, which strengthens the detection capability of radar for smaller targets. According to the sidelobes distributing characteristic, a method is presented in this paper to remove the estimated sidelobes mean value for signal detection after non-coherent integration. Simulation results present that the SNR of small target can be improved approximately 6. 5 dB by the proposed method.展开更多
Most solutions for detecting buffer overflow are based on source code. But the requirement tor source code is not always practical especially for business software. A new approach was presented to detect statically th...Most solutions for detecting buffer overflow are based on source code. But the requirement tor source code is not always practical especially for business software. A new approach was presented to detect statically the potential buffer overflow vulnerabilities in the binary code of software. The binary code was translated into assembly code without the lose of the information of string operation functions. The feature code abstract graph was constructed to generate more accurate constraint statements, and analyze the assembly code using the method of integer range constraint. After getting the elementary report on suspicious code where buffer overflows possibly happen, the control flow sensitive analysis using program dependence graph was done to decrease the rate of false positive. A prototype was implemented which demonstrates the feasibility and efficiency of the new approach.展开更多
A flexible field programmable gate array based radar signal processor is presented. The radar signal processor mainly consists of five functional modules： radar system timer, binary phase coded pulse compression（PC...A flexible field programmable gate array based radar signal processor is presented. The radar signal processor mainly consists of five functional modules： radar system timer, binary phase coded pulse compression（PC）, moving target detection （MTD）, constant false alarm rate （CFAR） and target dots processing. Preliminary target dots information is obtained in PC, MTD, and CFAR modules and Nios I! CPU is used for target dots combination and false sidelobe target removing. Sys- tem on programmable chip （SOPC） technique is adopted in the system in which SDRAM is used to cache data. Finally, a FPGA-based binary phase coded radar signal processor is realized and simula- tion result is given.展开更多
In the process of encoding and decoding,erasure codes over binary fields,which just need AND operations and XOR operations and therefore have a high computational efficiency,are widely used in various fields of inform...In the process of encoding and decoding,erasure codes over binary fields,which just need AND operations and XOR operations and therefore have a high computational efficiency,are widely used in various fields of information technology.A matrix decoding method is proposed in this paper.The method is a universal data reconstruction scheme for erasure codes over binary fields.Besides a pre-judgment that whether errors can be recovered,the method can rebuild sectors of loss data on a fault-tolerant storage system constructed by erasure codes for disk errors.Data reconstruction process of the new method has simple and clear steps,so it is beneficial for implementation of computer codes.And more,it can be applied to other non-binary fields easily,so it is expected that the method has an extensive application in the future.展开更多
Binary code signals have been widely used in various radars due to their simpleimplementation,but the selection of the binary codes with high comporession ratio and lowsidelobes is not solved well,because of the diffi...Binary code signals have been widely used in various radars due to their simpleimplementation,but the selection of the binary codes with high comporession ratio and lowsidelobes is not solved well,because of the difficult processing in mathmatics and expensivecalculation cost.In this paper,neural computing is introduced into the field of the selection ofbinary codes and a new method based’on simulated annealing(SA)is proposed.The experimentsshow that the proposed method is able to select the optimal binary codes with much less timecost than the known methods,furhtermore the optimization selection of the binary codes versusthe calculation cost tradeoff is easier.展开更多
A binary tree can be represented by a code reflecting the traversal of the corresponding regular binary tree in given monotonic order. A different coding scheme based on the branches of a regular binary tree with n-no...A binary tree can be represented by a code reflecting the traversal of the corresponding regular binary tree in given monotonic order. A different coding scheme based on the branches of a regular binary tree with n-nodes is proposed. It differs from the coding scheme generally used and makes no distinction between internal nodes and terminal nodes. A code of a regular binary tree with nnodes is formed by labeling the left branches by O’s and the right branches by l’s and then traversing these branches in pre-order. Root is always assumed to be on a left branch.展开更多
A novel coding based method named as local binary orientation code （LBOCode） for palmprint recognition is proposed. The palmprint image is firstly convolved with a bank of Gabor filters, and then the orientation inf...A novel coding based method named as local binary orientation code （LBOCode） for palmprint recognition is proposed. The palmprint image is firstly convolved with a bank of Gabor filters, and then the orientation information is attained with a winner-take-all rule. Subsequently, the resulting orientation mapping array is operated by uniform local binary pattern. Accordingly, LBOCode image is achieved which contains palmprint orientation information in pixel level. Further we divide the LBOCode image into several equal-size and nonoverlapping regions, and extract the statistical code histogram from each region independently, which builds a global description of palmprint in regional level. In matching stage, the matching score between two palmprints is achieved by calculating the two spatial enhanced histograms＇ dissimilarity, which brings the benefit of computational simplicity. Experimental results demonstrate that the proposed method achieves more promising recognition performance compared with that of several state-of-the-art methods.展开更多
Cyclic codes form an important class of codes. They have very interesting algebraic structure. Furthermore, they are equivalent to many important codes, such as binary Hamming codes, Golay codes and BCH codes. Minimal...Cyclic codes form an important class of codes. They have very interesting algebraic structure. Furthermore, they are equivalent to many important codes, such as binary Hamming codes, Golay codes and BCH codes. Minimal codewords in linear codes are widely used in constructing decoding algorithms and studying linear secret sharing scheme. In this paper, we show that in the binary cyclic code all of the codewords are minimal, except 0 and 1. Then, we obtain a result about the number of minimal codewords in the binary cyclic codes.展开更多
Monogenic binary coding （MBC） have been known to be effective for local feature extraction, while sparse or collaborative representation based classification （CRC） has shown interesting results in robust face reco...Monogenic binary coding （MBC） have been known to be effective for local feature extraction, while sparse or collaborative representation based classification （CRC） has shown interesting results in robust face recognition. In this paper, a novel face recognition algorithm of fusing MBC and CRC named M-CRC is proposed; in which the dimensionality problem is resolved by projection matrix. The proposed algorithm is evaluated on benchmark face databases, including AR, PolyU-NIR and CAS-PEAL. The results indicate a significant increase in the performance when compared with state-of-the-art face recognition methods.展开更多
This paper deals with the MIMO-OFDM technique that is applied to the fourth generation (4G) of the wireless communication systems, this technique can provide high data rate transmission without increasing transmit pow...This paper deals with the MIMO-OFDM technique that is applied to the fourth generation (4G) of the wireless communication systems, this technique can provide high data rate transmission without increasing transmit power and expanding bandwidth, it can also efficiently use space resources and has a bright future. It presents the channel coding assisted STBC-OFDM systems, and employs the Coded Modulation techniques (CM), since the signal bandwidth available for wireless communications is limited. The proposed system deals with Non-binary error control coding of the TCM-aided STBC-OFDM scheme for transmissions over the Rayleigh channel. A new non-binary decoding method, Yaletharatalhussein decoding algorithm, is designed and implemented for decoding non-binary convolutional codes, which is based on the trellis diagram representing the convolutional encoder. Yaletharatalhussein decoding algorithm outperforms the Viterbi algorithm and other algorithms in its simplicity, very small computational complexity, decoding reliability for high states TCM codes that are suitable for Fourth-Generation (4G), decreasing errors with increasing word length, and easy to implement with real-time applications. The simulation results show that the performance of the non-binary TCM-based Yaletharatalhussein decoding algorithm-assisted STBC-OFDM scheme outperforms the binary and non-binary decoding methods.展开更多
With the exponential development of mobile communications and the miniaturization of radio frequency transceivers, the need for small and low profile antennas at mobile frequencies is constantly growing. Therefore, ne...With the exponential development of mobile communications and the miniaturization of radio frequency transceivers, the need for small and low profile antennas at mobile frequencies is constantly growing. Therefore, new antennas should be developed to provide larger bandwidth and at the same time small dimensions. Although the gain in bandwidth performances of an antenna are directly related to its dimensions in relation to the wavelength, the aim is to keep the overall size of the antenna constant and from there, find the geometry and structure that give the best performance. The design and bandwidth optimization of a Planar Inverted-F Antenna (PIFA) were introduced in order to achieve a larger bandwidth in the 2 GHz band, using two optimization techniques based upon genetic algorithms (GA), namely the Binary Coded GA (BCGA) and Real-Coded GA (RCGA). During the optimization process, the different PIFA models were evaluated using the finite-difference time domain (FDTD) method-a technique belonging to the general class of differential time domain numerical modeling methods.展开更多
文摘Binary Code Similarity Detection(BCSD)is vital for vulnerability discovery,malware detection,and software security,especially when source code is unavailable.Yet,it faces challenges from semantic loss,recompilation variations,and obfuscation.Recent advances in artificial intelligence—particularly natural language processing(NLP),graph representation learning(GRL),and large language models(LLMs)—have markedly improved accuracy,enabling better recognition of code variants and deeper semantic understanding.This paper presents a comprehensive review of 82 studies published between 1975 and 2025,systematically tracing the historical evolution of BCSD and analyzing the progressive incorporation of artificial intelligence(AI)techniques.Particular emphasis is placed on the role of LLMs,which have recently emerged as transformative tools in advancing semantic representation and enhancing detection performance.The review is organized around five central research questions:(1)the chronological development and milestones of BCSD;(2)the construction of AI-driven technical roadmaps that chart methodological transitions;(3)the design and implementation of general analytical workflows for binary code analysis;(4)the applicability,strengths,and limitations of LLMs in capturing semantic and structural features of binary code;and(5)the persistent challenges and promising directions for future investigation.By synthesizing insights across these dimensions,the study demonstrates how LLMs reshape the landscape of binary code analysis,offering unprecedented opportunities to improve accuracy,scalability,and adaptability in real-world scenarios.This review not only bridges a critical gap in the existing literature but also provides a forward-looking perspective,serving as a valuable reference for researchers and practitioners aiming to advance AI-powered BCSD methodologies and applications.
基金supported by Key Laboratory of Cyberspace Security,Ministry of Education,China。
文摘Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Although adversarial examples can strategically undermine the accuracy of BCSD models and protect critical code,existing techniques predominantly depend on inserting artificial instructions,which incur high computational costs and offer limited diversity of perturbations.To address these limitations,we propose AIMA,a novel gradient-guided assembly instruction relocation method.Our method decouples the detection model into tokenization,embedding,and encoding layers to enable efficient gradient computation.Since token IDs of instructions are discrete and nondifferentiable,we compute gradients in the continuous embedding space to evaluate the influence of each token.The most critical tokens are identified by calculating the L2 norm of their embedding gradients.We then establish a mapping between instructions and their corresponding tokens to aggregate token-level importance into instructionlevel significance.To maximize adversarial impact,a sliding window algorithm selects the most influential contiguous segments for relocation,ensuring optimal perturbation with minimal length.This approach efficiently locates critical code regions without expensive search operations.The selected segments are relocated outside their original function boundaries via a jump mechanism,which preserves runtime control flow and functionality while introducing“deletion”effects in the static instruction sequence.Extensive experiments show that AIMA reduces similarity scores by up to 35.8%in state-of-the-art BCSD models.When incorporated into training data,it also enhances model robustness,achieving a 5.9%improvement in AUROC.
基金Supported by the National Natural Science Foundation of China
文摘A decoding algorithm based on revised syndromes to decode the binary (23,12,7) Golay code is presented. The algorithm strongly depends on the algebraic properties of the code. For the algorithm, the worst complexity is about 683 mod2 additions, which is less than that of the algorithms available for the code, the average complexity is approximately 319 mod2 additions, which is slightly more than that of Blaum’s algorithm for the code.
基金supported in part by National Natural Science Foundation of China(No.62471054)in part by National Natural Science Foundation of China(No.92467301)+3 种基金in part by the National Natural Science Foundation of China(No.62201562)in part by the National Natural Science Foundation of China(No.62371063)in part by the National Natural Science Foundation of China(No.62321001)in part by Liaoning Provincial Natural Science Foundation of China(No.2024–BSBA–51).
文摘In 5G new radio(NR), polar codes are adopted for e MBB downlink control channels where the blind detection is employed in user equipment(UE) to identify the correct downlink control information(DCI). However, different from that in the 4G LTE system, the cyclic redundancy check(CRC) in polar decoding plays both error correction and error detection roles. Consequently, the false alarm rates(FAR) may not meet the system requirements(FAR<1.52 × 10^(−5)). In this paper, to mitigate the FAR in polar code blind detection, we attach a binary classifier after the polar decoder to further remove the false alarm results and meanwhile retain the correct DCI. This classifier works by tracking the squared Euclidean distance ratio(SEDR) between the received signal and hypothesis. We derive an analytical method to fast compute proper classification threshold that is implementation-friendly in practical use. Combining the well-designed classifier, we show that some very short CRC sequences can even be used to meet the FAR requirements. This consequently reduces the CRC overhead and contributes to the system error performance improvements.
文摘A new non-binary decoding method, which is called Yaletharatalhussein decoding algorithm, is designed and implemented for decoding non-binary convolutional codes which is based on the trellis diagram representing the convolutional encoder. Yaletharatalhussein decoding algorithm outperforms the Viterbi algorithm and other algorithms in its simplicity, very small computational complexity, decoding reliability for high states TCM codes that suitable for Fourth-Generation (4G), decreasing errors with increasing word length, and easy to implement with real-time applications. The proposed Yaletharatalhussein decoding algorithm deals with non-binary error control coding of the convolutional and TCM codes. Convolutional codes differ from block codes in that a block code takes a fixed message length and encodes it, whereas a convolutional code can encode a continuous stream of data, and a hard-decision decoding can easily be realized using the Yaletharatalhussein algorithm. The idea of non-binary codes has been extended for symbols defined over rings of integers, which outperform binary codes with only a small increase in decoding complexity. The simulation results show that the performance of the nonbinary TCM-based Yaletharatalhussein algorithm outperforms the binary and non-binary decoding methods.
文摘In this paper, a statistical recognition method of the binary BCH code is proposed. The method is applied to both primitive and non-primitive binary BCH code. The block length is first recognized based on the cyclic feature under the condition of the frame length known. And then candidate polynomials are achieved which meet the restrictions. Among the candidate polynomials, the most optimal polynomial is selected based on the minimum rule of the weights sum of the syndromes. Finally, the best polynomial was factorized to get the generator polynomial recognized. Simulation results show that the method has strong capability of anti-random bit error. Besides, the algorithm proposed is very simple, so it is very practical for hardware im-plementation.
基金Supported by the National Natural Science Foundation of China(Youth Science Fund)(61001190)
文摘The m series with 511 bits is taken as an example being applied in non-coherent integra- tion algorithm. A method to choose the bi-phase code is presented, which is 15 kinds of codes are picked out of 511 kinds of m series to do non-coherent integration. It is indicated that the power in- creasing times of larger target sidelobe is less than the power increasing times of smaller target main- lobe because of the larger target＇ s pseudo-randomness. Smaller target is integrated from larger tar- get sidelobe, which strengthens the detection capability of radar for smaller targets. According to the sidelobes distributing characteristic, a method is presented in this paper to remove the estimated sidelobes mean value for signal detection after non-coherent integration. Simulation results present that the SNR of small target can be improved approximately 6. 5 dB by the proposed method.
文摘Most solutions for detecting buffer overflow are based on source code. But the requirement tor source code is not always practical especially for business software. A new approach was presented to detect statically the potential buffer overflow vulnerabilities in the binary code of software. The binary code was translated into assembly code without the lose of the information of string operation functions. The feature code abstract graph was constructed to generate more accurate constraint statements, and analyze the assembly code using the method of integer range constraint. After getting the elementary report on suspicious code where buffer overflows possibly happen, the control flow sensitive analysis using program dependence graph was done to decrease the rate of false positive. A prototype was implemented which demonstrates the feasibility and efficiency of the new approach.
基金Supported by the Ministerial Level Advanced Research Foundation (SP240012)
文摘A flexible field programmable gate array based radar signal processor is presented. The radar signal processor mainly consists of five functional modules： radar system timer, binary phase coded pulse compression（PC）, moving target detection （MTD）, constant false alarm rate （CFAR） and target dots processing. Preliminary target dots information is obtained in PC, MTD, and CFAR modules and Nios I! CPU is used for target dots combination and false sidelobe target removing. Sys- tem on programmable chip （SOPC） technique is adopted in the system in which SDRAM is used to cache data. Finally, a FPGA-based binary phase coded radar signal processor is realized and simula- tion result is given.
基金supported by the National Natural Science Foundation of China under Grant No.61501064Sichuan Provincial Science and Technology Project under Grant No.2016GZ0122
文摘In the process of encoding and decoding,erasure codes over binary fields,which just need AND operations and XOR operations and therefore have a high computational efficiency,are widely used in various fields of information technology.A matrix decoding method is proposed in this paper.The method is a universal data reconstruction scheme for erasure codes over binary fields.Besides a pre-judgment that whether errors can be recovered,the method can rebuild sectors of loss data on a fault-tolerant storage system constructed by erasure codes for disk errors.Data reconstruction process of the new method has simple and clear steps,so it is beneficial for implementation of computer codes.And more,it can be applied to other non-binary fields easily,so it is expected that the method has an extensive application in the future.
文摘Binary code signals have been widely used in various radars due to their simpleimplementation,but the selection of the binary codes with high comporession ratio and lowsidelobes is not solved well,because of the difficult processing in mathmatics and expensivecalculation cost.In this paper,neural computing is introduced into the field of the selection ofbinary codes and a new method based’on simulated annealing(SA)is proposed.The experimentsshow that the proposed method is able to select the optimal binary codes with much less timecost than the known methods,furhtermore the optimization selection of the binary codes versusthe calculation cost tradeoff is easier.
文摘A binary tree can be represented by a code reflecting the traversal of the corresponding regular binary tree in given monotonic order. A different coding scheme based on the branches of a regular binary tree with n-nodes is proposed. It differs from the coding scheme generally used and makes no distinction between internal nodes and terminal nodes. A code of a regular binary tree with nnodes is formed by labeling the left branches by O’s and the right branches by l’s and then traversing these branches in pre-order. Root is always assumed to be on a left branch.
基金supported partly by the National Grand Fundamental Research 973 Program of China under Grant No. 2004CB318005the Doctoral Candidate Outstanding Innovation Foundation under Grant No.141092522the Fundamental Research Funds under Grant No.2009YJS025
文摘A novel coding based method named as local binary orientation code （LBOCode） for palmprint recognition is proposed. The palmprint image is firstly convolved with a bank of Gabor filters, and then the orientation information is attained with a winner-take-all rule. Subsequently, the resulting orientation mapping array is operated by uniform local binary pattern. Accordingly, LBOCode image is achieved which contains palmprint orientation information in pixel level. Further we divide the LBOCode image into several equal-size and nonoverlapping regions, and extract the statistical code histogram from each region independently, which builds a global description of palmprint in regional level. In matching stage, the matching score between two palmprints is achieved by calculating the two spatial enhanced histograms＇ dissimilarity, which brings the benefit of computational simplicity. Experimental results demonstrate that the proposed method achieves more promising recognition performance compared with that of several state-of-the-art methods.
文摘Cyclic codes form an important class of codes. They have very interesting algebraic structure. Furthermore, they are equivalent to many important codes, such as binary Hamming codes, Golay codes and BCH codes. Minimal codewords in linear codes are widely used in constructing decoding algorithms and studying linear secret sharing scheme. In this paper, we show that in the binary cyclic code all of the codewords are minimal, except 0 and 1. Then, we obtain a result about the number of minimal codewords in the binary cyclic codes.
文摘Monogenic binary coding （MBC） have been known to be effective for local feature extraction, while sparse or collaborative representation based classification （CRC） has shown interesting results in robust face recognition. In this paper, a novel face recognition algorithm of fusing MBC and CRC named M-CRC is proposed; in which the dimensionality problem is resolved by projection matrix. The proposed algorithm is evaluated on benchmark face databases, including AR, PolyU-NIR and CAS-PEAL. The results indicate a significant increase in the performance when compared with state-of-the-art face recognition methods.
文摘This paper deals with the MIMO-OFDM technique that is applied to the fourth generation (4G) of the wireless communication systems, this technique can provide high data rate transmission without increasing transmit power and expanding bandwidth, it can also efficiently use space resources and has a bright future. It presents the channel coding assisted STBC-OFDM systems, and employs the Coded Modulation techniques (CM), since the signal bandwidth available for wireless communications is limited. The proposed system deals with Non-binary error control coding of the TCM-aided STBC-OFDM scheme for transmissions over the Rayleigh channel. A new non-binary decoding method, Yaletharatalhussein decoding algorithm, is designed and implemented for decoding non-binary convolutional codes, which is based on the trellis diagram representing the convolutional encoder. Yaletharatalhussein decoding algorithm outperforms the Viterbi algorithm and other algorithms in its simplicity, very small computational complexity, decoding reliability for high states TCM codes that are suitable for Fourth-Generation (4G), decreasing errors with increasing word length, and easy to implement with real-time applications. The simulation results show that the performance of the non-binary TCM-based Yaletharatalhussein decoding algorithm-assisted STBC-OFDM scheme outperforms the binary and non-binary decoding methods.
文摘With the exponential development of mobile communications and the miniaturization of radio frequency transceivers, the need for small and low profile antennas at mobile frequencies is constantly growing. Therefore, new antennas should be developed to provide larger bandwidth and at the same time small dimensions. Although the gain in bandwidth performances of an antenna are directly related to its dimensions in relation to the wavelength, the aim is to keep the overall size of the antenna constant and from there, find the geometry and structure that give the best performance. The design and bandwidth optimization of a Planar Inverted-F Antenna (PIFA) were introduced in order to achieve a larger bandwidth in the 2 GHz band, using two optimization techniques based upon genetic algorithms (GA), namely the Binary Coded GA (BCGA) and Real-Coded GA (RCGA). During the optimization process, the different PIFA models were evaluated using the finite-difference time domain (FDTD) method-a technique belonging to the general class of differential time domain numerical modeling methods.
