Simple PSF based method for pupil phase mask’s optimization in wavefront coding system

By applying the wavefront coding technique to an optical system, the depth of focus can be greatly increased. Several complicated methods, such as Fisher Information based method, have already been taken to optimize for the best pupil phase mask in ideal condition. Here one simple point spread function (PSF) based method with only the standard deviation method used to evaluate the PSF stability over the depth of focus is taken to optimize for the best coefficients of pupil phase mask in practical optical systems. Results of imaging simulations for optical systems with and without pupil phase mask are presented, and the sharpness of image is calculated for comparison. The optimized results showed better and much more stable imaging quality over the original system without changing the position of the image plane.

JOINT ITERATIVE DECODING FOR SIMPLE-ENCODING SYSTEMATIC IRREGULAR-LDPC-BASED CODED COOPERATION IN NON-IDEAL RELAY CHANNEL

In this paper, a new kind of simple-encoding irregular systematic LDPC codes suitable for one-relay coded cooperation is designed, where the proposed joint iterative decoding is effectively performed in the destination which is in accordance with the corresponding joint Tanner graph characterizing two different component LDPC codes used by the source and relay in ideal and non-ideal relay cooperations. The theoretical analysis and simulations show that the coded cooperation scheme obviously outperforms the coded non-cooperation one under the same code rate and decoding complex. The significant performance improvement can be virtually credited to the additional mutual exchange of the extrinsic information resulted by the LDPC code employed by the source and its counterpart used by the relay in both ideal and non-ideal cooperations.

A New Arithmetic Coding System Combining Source Channel Coding and MAP Decoding

A new arithmetic coding system combining source channel coding and maximum a posteriori decoding were proposed. It combines source coding and error correction tasks into one unified process by introducing an adaptive forbidden symbol. The proposed system achieves fixed length code words by adaptively adjusting the probability of the forbidden symbol and adding tail digits of variable length. The corresponding improved MAP decoding metric was derived. The proposed system can improve the performance. Simulations were performed on AWGN channels with various noise levels by using both hard and soft decision with BPSK modulation.The results show its performance is slightly better than that of our adaptive arithmetic error correcting coding system using a forbidden symbol.

PIC-MF-based Iterative Receiver for Multiuser Space Frequency Block Coding Systems

A novel low-complexity iterative receiver for multiuser space frequency block coding (SFBC) system was proposed in this paper. Unlike the conventional linear minimum mean square error (MMSE) detector, which requires matrix inversion at each iteration, the soft-in soft-out (SISO) detector is simply a parallel interference cancellation (PIC)-matched filter (MF) operation. The probability density function (PDF) of PIC-MF detector output is approximated as Gaussian, whose variance is calculated with a priori information fed back from the channel decoder. With this approximation, the log likelihood ratios (LLRs) of transmitted bits are under-estimated. Then the LLRs are multiplied by a constant factor to achieve a performance gain. The constant factor is optimized according to extrinsic information transfer (EXIT) chart of the SISO detector. Simulation results show that the proposed iterative receiver can significantly improve the system performance and converge to the matched filter bound (MFB) with low computational complexity at high signal-to-noise ratios (SNRs).

An Iterative Power Allocation Algorithm for Group-wise Space-Time Block Coding Systems

An iterative transmit power allocation (PA) algorithm was proposed for group-wise space-time block coding (G-STBC) systems with group-wise successive interference cancellation (GSIC) receivers. Group-wise interference suppression (GIS) filters are employed to separate each group's transmit signals from other interferences and noise. While the total power on all transmit symbols is constrained, all transmit PA coefficients are updated jointly according to the channel information at each iteration. Through PA, each detection symbol has the same post-detection signal to interference-and-noise ratio (SINR). The simulation results verify that the proposed PA algorithm converges at the equilibrium quickly after few iterations, and it achieves much lower bit error rates than the previous single symbol SIC PA and the fixed ratio PA algorithms for G-STBC systems with GSIC receivers .

An apodized cubic phase mask used in a wavefront coding system to extend the depth of field

The point spread function(PSF)caused by a wavefront coding system with a cubic phase mask has big side-lobes which leads to bad image restoration.This paper proposes a novel apodized cubic phase mask to suppress the side-lobes of the PSF.Simulated annealing algorithm is used to optimize the cubic and the truncation parameter of the phase mask.The system with the novel phase mask has better performance in the modulation transfer function(MTF)especially in low-and-medium spatial frequency region.The simulation results show that the restored images with the novel phase mask are superior to the one with the classic cubic phase mask in contrast and ringing effect.The experimental results show that the side-lobes of the PSF are suppressed by using the apodized cubic phase mask.

Optical transfer function analysis of circular-pupil wavefront coding systems with separable phase masks

This paper proposes a simple method to achieve the optical transfer function of a circular pupil wavefront coding system with a separable phase mask in Cartesian coordinates. Based on the stationary phase method, the optical transfer function of the circular pupil system can be easily obtained from the optical transfer function of the rectangular pupil system by modifying the cut-off frequency and the on-axial modulation transfer function. Finally, a system with a cubic phase mask is used as an example to illustrate the way to achieve the optical transfer function of the circular pupil system from the rectangular pupil system.

An Efficient Compression Coding System for Motion Images

An efficient compression coding system for motion images is presented. A macro-block matchingtechnique based on tile correlation betweell motion vectors is applied to the system. This technique effectivelyimproves the accuracy and the speed of motion estimation, and the compression ratio. A compression ratio of 29 isattainable without visible image degradation.

New Applications of EXIT Chart for Iterative Decoding Systems

Applications on iterative control and multiple input multiple output (MIMO) system were developed. Two new charts derived from extrinsic information transfer (EXIT) chart were employed as the designing tools, which are called as output mutual information chart with defined iterative degree (DID) chart and near optimum output mutual information (NOMI) chart respectively. Different from the EXIT chart, they can show the iterative performance on the whole signal-to-noise ratio range with one single curve, whereas computation complexity is greatly reduced compared with conventional bit error ratio (BER) performance curve. The iterative control was implemented according to a near-optimum iterative degree vector determined by NOMI chart, the reasonability of uncertain parameters was analyzed in one MIMO system. The concepts were illustrated based on bit-interleaved coded modulation with iterative decoding (BICM-ID).

Performance Evaluation of OFDM Coding System Using Concatenated BCH and LDPC Codes

This paper establishes a resilient concatenated coding platform for Orthogonal Frequency Division Multiplexing (OFDM) with Quadrature Amplitude Modulation (QAM) over Additive White Gaussian Noise (AWGN) channel. At the Forward Error Correction (FEC) coding unit, our proposed concatenated coding scheme utilizes standard type of BCH as external coding and LDPC as inner coding. In this scheme, Interleaver inclusion is seen as a catalyst to enhance the systems performance.

Research on a New Coding System for Vibrating Feeder Design

The sUdeway design is the key in the design of the disc vibrating feeder. However, no reliable theoretical guidance has come into existence, which greatly restricted the application of CAD（ Computer-aided design）. In order to feed the application of CAD technology, we must make improvements to the existing coding method. Based on the similarity principle of Group Technology and existing coding system, a new coding method applicable to slide- way design is brought forward. The existing coding system could get optimized by means of analysing and studying the influence imposed by the parts＇ shape and posture features. More detailed information about the parts could be supplied by the new coding system, which makes the design simpler, more convenient and more accurate with the subjoin of the initial and targeted codes.

Design of Protograph LDPC-Coded MIMO-VLC Systems with Generalized Spatial Modulation

This paper investigates the bit-interleaved coded generalized spatial modulation(BICGSM) with iterative decoding(BICGSM-ID) for multiple-input multiple-output(MIMO) visible light communications(VLC). In the BICGSM-ID scheme, the information bits conveyed by the signal-domain(SiD) symbols and the spatial-domain(SpD) light emitting diode(LED)-index patterns are coded by a protograph low-density parity-check(P-LDPC) code. Specifically, we propose a signal-domain symbol expanding and re-allocating(SSER) method for constructing a type of novel generalized spatial modulation(GSM) constellations, referred to as SSERGSM constellations, so as to boost the performance of the BICGSM-ID MIMO-VLC systems.Moreover, by applying a modified PEXIT(MPEXIT) algorithm, we further design a family of rate-compatible P-LDPC codes, referred to as enhanced accumulate-repeat-accumulate(EARA) codes,which possess both excellent decoding thresholds and linear-minimum-distance-growth property. Both analysis and simulation results illustrate that the proposed SSERGSM constellations and P-LDPC codes can remarkably improve the convergence and decoding performance of MIMO-VLC systems. Therefore, the proposed P-LDPC-coded SSERGSM-mapped BICGSMID configuration is envisioned as a promising transmission solution to satisfy the high-throughput requirement of MIMO-VLC applications.

Intrusion Detection Model Using Chaotic MAP for Network Coding Enabled Mobile Small Cells

Wireless Network security management is difficult because of the ever-increasing number of wireless network malfunctions,vulnerabilities,and assaults.Complex security systems,such as Intrusion Detection Systems(IDS),are essential due to the limitations of simpler security measures,such as cryptography and firewalls.Due to their compact nature and low energy reserves,wireless networks present a significant challenge for security procedures.The features of small cells can cause threats to the network.Network Coding(NC)enabled small cells are vulnerable to various types of attacks.Avoiding attacks and performing secure“peer”to“peer”data transmission is a challenging task in small cells.Due to the low power and memory requirements of the proposed model,it is well suited to use with constrained small cells.An attacker cannot change the contents of data and generate a new Hashed Homomorphic Message Authentication Code(HHMAC)hash between transmissions since the HMAC function is generated using the shared secret.In this research,a chaotic sequence mapping based low overhead 1D Improved Logistic Map is used to secure“peer”to“peer”data transmission model using lightweight H-MAC(1D-LM-P2P-LHHMAC)is proposed with accurate intrusion detection.The proposed model is evaluated with the traditional models by considering various evaluation metrics like Vector Set Generation Accuracy Levels,Key Pair Generation Time Levels,Chaotic Map Accuracy Levels,Intrusion Detection Accuracy Levels,and the results represent that the proposed model performance in chaotic map accuracy level is 98%and intrusion detection is 98.2%.The proposed model is compared with the traditional models and the results represent that the proposed model secure data transmission levels are high.

A quantum blind signature scheme based on dense coding for non-entangled states

In some schemes, quantum blind signatures require the use of difficult-to-prepare multiparticle entangled states. By considering the communication overhead, quantum operation complexity, verification efficiency and other relevant factors in practical situations, this article proposes a non-entangled quantum blind signature scheme based on dense encoding. The information owner utilizes dense encoding and hash functions to blind the information while reducing the use of quantum resources. After receiving particles, the signer encrypts the message using a one-way function and performs a Hadamard gate operation on the selected single photon to generate the signature. Then the verifier performs a Hadamard gate inverse operation on the signature and combines it with the encoding rules to restore the message and complete the verification.Compared with some typical quantum blind signature protocols, this protocol has strong blindness in privacy protection,and higher flexibility in scalability and application. The signer can adjust the signature operation according to the actual situation, which greatly simplifies the complexity of the signature. By simultaneously utilizing the secondary distribution and rearrangement of non-entangled quantum states, a non-entangled quantum state representation of three bits of classical information is achieved, reducing the use of a large amount of quantum resources and lowering implementation costs. This improves both signature verification efficiency and communication efficiency while, at the same time, this scheme meets the requirements of unforgeability, non-repudiation, and prevention of information leakage.

Single Photon Detection Technology in Underwater Wireless Optical Communication:Modulation Modes and Error Correction Coding Analysis

This study explores the application of single photon detection(SPD)technology in underwater wireless optical communication(UWOC)and analyzes the influence of different modulation modes and error correction coding types on communication performance.The study investigates the impact of on-off keying(OOK)and 2-pulse-position modulation(2-PPM)on the bit error rate(BER)in single-channel intensity and polarization multiplexing.Furthermore,it compares the error correction performance of low-density parity check(LDPC)and Reed-Solomon(RS)codes across different error correction coding types.The effects of unscattered photon ratio and depolarization ratio on BER are also verified.Finally,a UWOC system based on SPD is constructed,achieving 14.58 Mbps with polarization OOK multiplexing modulation and 4.37 Mbps with polarization 2-PPM multiplexing modulation using LDPC code error correction.

Variational Learned Talking-Head Semantic Coded Transmission System

Video transmission requires considerable bandwidth,and current widely employed schemes prove inadequate when confronted with scenes featuring prominently.Motivated by the strides in talkinghead generative technology,the paper introduces a semantic transmission system tailored for talking-head videos.The system captures semantic information from talking-head video and faithfully reconstructs source video at the receiver,only one-shot reference frame and compact semantic features are required for the entire transmission.Specifically,we analyze video semantics in the pixel domain frame-by-frame and jointly process multi-frame semantic information to seamlessly incorporate spatial and temporal information.Variational modeling is utilized to evaluate the diversity of importance among group semantics,thereby guiding bandwidth resource allocation for semantics to enhance system efficiency.The whole endto-end system is modeled as an optimization problem and equivalent to acquiring optimal rate-distortion performance.We evaluate our system on both reference frame and video transmission,experimental results demonstrate that our system can improve the efficiency and robustness of communications.Compared to the classical approaches,our system can save over 90%of bandwidth when user perception is close.

Image encryption algorithm based on multiple chaotic systems and improved Joseph block scrambling

With the rapid development of digital information technology,images are increasingly used in various fields.To ensure the security of image data,prevent unauthorized tampering and leakage,maintain personal privacy,and protect intellectual property rights,this study proposes an innovative color image encryption algorithm.Initially,the Mersenne Twister algorithm is utilized to generate high-quality pseudo-random numbers,establishing a robust basis for subsequent operations.Subsequently,two distinct chaotic systems,the autonomous non-Hamiltonian chaotic system and the tentlogistic-cosine chaotic mapping,are employed to produce chaotic random sequences.These chaotic sequences are used to control the encoding and decoding process of the DNA,effectively scrambling the image pixels.Furthermore,the complexity of the encryption process is enhanced through improved Joseph block scrambling.Thorough experimental verification,research,and analysis,the average value of the information entropy test data reaches as high as 7.999.Additionally,the average value of the number of pixels change rate(NPCR)test data is 99.6101%,which closely approaches the ideal value of 99.6094%.This algorithm not only guarantees image quality but also substantially raises the difficulty of decryption.

HCRVD: A Vulnerability Detection System Based on CST-PDG Hierarchical Code Representation Learning

Prior studies have demonstrated that deep learning-based approaches can enhance the performance of source code vulnerability detection by training neural networks to learn vulnerability patterns in code representations.However,due to limitations in code representation and neural network design,the validity and practicality of the model still need to be improved.Additionally,due to differences in programming languages,most methods lack cross-language detection generality.To address these issues,in this paper,we analyze the shortcomings of previous code representations and neural networks.We propose a novel hierarchical code representation that combines Concrete Syntax Trees(CST)with Program Dependence Graphs(PDG).Furthermore,we introduce a Tree-Graph-Gated-Attention(TGGA)network based on gated recurrent units and attention mechanisms to build a Hierarchical Code Representation learning-based Vulnerability Detection(HCRVD)system.This system enables cross-language vulnerability detection at the function-level.The experiments show that HCRVD surpasses many competitors in vulnerability detection capabilities.It benefits from the hierarchical code representation learning method,and outperforms baseline in cross-language vulnerability detection by 9.772%and 11.819%in the C/C++and Java datasets,respectively.Moreover,HCRVD has certain ability to detect vulnerabilities in unknown programming languages and is useful in real open-source projects.HCRVD shows good validity,generality and practicality.

Systematic Review: Analysis of Coding Vulnerabilities across Languages

The boom of coding languages in the 1950s revolutionized how our digital world was construed and accessed. The languages invented then, including Fortran, are still in use today due to their versatility and ability to underpin a large majority of the older portions of our digital world and applications. Fortran, or Formula Translation, was a programming language implemented by IBM that shortened the apparatus of coding and the efficacy of the language syntax. Fortran marked the beginning of a new era of efficient programming by reducing the number of statements needed to operate a machine several-fold. Since then, dozens more languages have come into regular practice and have been increasingly diversified over the years. Some modern languages include Python, Java, JavaScript, C, C++, and PHP. These languages significantly improved efficiency and also have a broad range of uses. Python is mainly used for website/software development, data analysis, task automation, image processing, and graphic design applications. On the other hand, Java is primarily used as a client-side programming language. Expanding the coding languages allowed for increasing accessibility but also opened up applications to pertinent security issues. These security issues have varied by prevalence and language. Previous research has narrowed its focus on individual languages, failing to evaluate the security. This research paper investigates the severity and frequency of coding vulnerabilities comparatively across different languages and contextualizes their uses in a systematic literature review.

Decoding topological XYZ^(2) codes with reinforcement learning based on attention mechanisms

Quantum error correction, a technique that relies on the principle of redundancy to encode logical information into additional qubits to better protect the system from noise, is necessary to design a viable quantum computer. For this new topological stabilizer code-XYZ^(2) code defined on the cellular lattice, it is implemented on a hexagonal lattice of qubits and it encodes the logical qubits with the help of stabilizer measurements of weight six and weight two. However topological stabilizer codes in cellular lattice quantum systems suffer from the detrimental effects of noise due to interaction with the environment. Several decoding approaches have been proposed to address this problem. Here, we propose the use of a state-attention based reinforcement learning decoder to decode XYZ^(2) codes, which enables the decoder to more accurately focus on the information related to the current decoding position, and the error correction accuracy of our reinforcement learning decoder model under the optimisation conditions can reach 83.27% under the depolarizing noise model, and we have measured thresholds of 0.18856 and 0.19043 for XYZ^(2) codes at code spacing of 3–7 and 7–11, respectively. our study provides directions and ideas for applications of decoding schemes combining reinforcement learning attention mechanisms to other topological quantum error-correcting codes.