Angular Momentum (AM) has been considered as a new dimension of wireless transmissions as well as the intrinsic property of Electro-Magnetic (EM) waves. So far, AM is utilized as a discrete mode not only in the quantum states, but also in the statistical beam forming. Traditionally, the continuous value of AM is ignored and only the quantized mode number is identified. However, the recent discovery on electrons in spiral motion producing twisted radiation with AM, including Spin Angular Momentum (SAM) and Orbital Angular Momentum (OAM), proves that the continuous value of AM is available in the statistical EM wave beam. This is also revealed by the so-called fractional OAM, which is reported in optical OAM beams. Then, as the new dimension with continuous real number field, AM should turn out to be a certain spectrum, similar to the frequency spectrum usually in the wireless signal processing. In this letter, we mathematically define the AM spectrum and show the applications in the information theory analysis, which is expected to be an efficient tool for the future wireless communications with AM.

The reliability of deep neural networks (DNN) against hardware errors is essential as DNNs are increasingly employed in safety-critical applications such as automatic driving. Transient errors in memory, such as radiation-induced soft error, may propagate through the inference computation, resulting in unexpected output, which can adversely trigger catastrophic system failures. As a first step to tackle this problem, this paper proposes constructing a vulnerability model (VM) with a small number of fault injections to identify vulnerable model parameters in DNN. We reduce the number of bit locations for fault injection significantly and develop a flow to incrementally collect the training data, i.e., the fault injection results, for VM accuracy improvement. We enumerate key features (KF) that characterize the vulnerability of the parameters and use KF and the collected training data to construct VM. Experimental results show that VM can estimate vulnerabilities of all DNN model parameters only with 1/3490 computations compared with traditional fault injection-based vulnerability estimation.

Let f be a Boolean function in n variables. The Möbius transform and its converse of f can describe the transformation behaviors between the truth table of f and the coefficients of the monomials in the algebraic normal form representation of f. In this letter, we develop the Möbius transform and its converse into a more generalized form, which also includes the known result given by Reed in 1954. We hope that our new result can be used in the design of decoding schemes for linear codes and the cryptanalysis for symmetric cryptography. We also apply our new result to verify the basic idea of the cube attack in a very simple way, in which the cube attack is a powerful technique on the cryptanalysis for symmetric cryptography.

In this paper, we present a novel photometric compensation network named CASEformer, which is built upon the Swin module. For the first time, we combine coordinate attention and channel attention mechanisms to extract rich features from input images. Employing a multi-level encoder-decoder architecture with skip connections, we establish multiscale interactions between projection surfaces and projection images, achieving precise inference and compensation. Furthermore, through an attention fusion module, which simultaneously leverages both coordinate and channel information, we enhance the global context of feature maps while preserving enhanced texture coordinate details. The experimental results demonstrate the superior compensation effectiveness of our approach compared to the current state-of-the-art methods. Additionally, we propose a method for multi-surface projection compensation, further enriching our contributions.

In the advanced digital terrestrial/television multimedia broadcasting (DTMB-A) standard, a preamble based on distance detection (PBDD) is adopted for robust synchronization and signalling transmission. However, traditional signalling detection method will completely fail to work under severe frequency selective channels with ultra-long delay spread 0dB echoes. In this paper, a novel transmission parameter signalling detection method is proposed for the preamble in DTMB-A. Compared with the conventional signalling detection method, the proposed scheme works much better when the maximum channel delay is close to the length of the guard interval (GI). Both theoretical analyses and simulation results demonstrate that the proposed algorithm significantly improves the accuracy and robustness of detecting the transmitted signalling.

In recent decade, many state-of-the-art algorithms on image classification as well as audio classification have achieved noticeable successes with the development of deep convolutional neural network (CNN). However, most of the works only exploit single type of training data. In this paper, we present a study on classifying bird species by exploiting the combination of both visual (images) and audio (sounds) data using CNN, which has been sparsely treated so far. Specifically, we propose CNN-based multimodal learning models in three types of fusion strategies (early, middle, late) to settle the issues of combining training data cross domains. The advantage of our proposed method lies on the fact that we can utilize CNN not only to extract features from image and audio data (spectrogram) but also to combine the features across modalities. In the experiment, we train and evaluate the network structure on a comprehensive CUB-200-2011 standard data set combing our originally collected audio data set with respect to the data species. We observe that a model which utilizes the combination of both data outperforms models trained with only an either type of data. We also show that transfer learning can significantly increase the classification performance.

In this paper, we address the problem of non-parametric template matching which does not assume any specific deformation models. In real-world matching scenarios, deformation between a template and a matching result usually appears to be non-rigid and non-linear. We propose a novel approach called local rigidity constraints (LRC). LRC is built based on an assumption that the local rigidity, which is referred to as structural persistence between image patches, can help the algorithm to achieve better performance. A spatial relation test is proposed to weight the rigidity between two image patches. When estimating visual similarity under an unconstrained environment, high-level similarity (e.g. with complex geometry transformations) can then be estimated by investigating the number of LRC. In the searching step, exhaustive matching is possible because of the simplicity of the algorithm. Global maximum is given out as the final matching result. To evaluate our method, we carry out a comprehensive comparison on a publicly available benchmark and show that our method can outperform the state-of-the-art method.

In this paper, we address the problem of projective template matching which aims to estimate parameters of projective transformation. Although homography can be estimated by combining key-point-based local features and RANSAC, it can hardly be solved with feature-less images or high outlier rate images. Estimating the projective transformation remains a difficult problem due to high-dimensionality and strong non-convexity. Our approach is to quantize the parameters of projective transformation with binary finite field and search for an appropriate solution as the final result over the discrete sampling set. The benefit is that we can avoid searching among a huge amount of potential candidates. Furthermore, in order to approximate the global optimum more efficiently, we develop a level-wise adaptive sampling (LAS) method under genetic algorithm framework. With LAS, the individuals are uniformly selected from each fitness level and the elite solution finally converges to the global optimum. In the experiment, we compare our method against the popular projective solution and systematically analyse our method. The result shows that our method can provide convincing performance and holds wider application scope.

This paper describes a method to evaluate the modulated waveforms output by a high-speed external phase modulator over a wide wavelength range by using linear optical sampling (LOS) and a wavelength-swept light source. The phase-modulated waveform is sampled by LOS together with the reference signal before modulation, and the modulation waveform is observed by removing the phase noise of the light source extracted from the reference signal. In this process, the frequency offset caused by the optical-path length difference between the measurement and reference interferometers is removed by digital signal processing. A pseudo-random binary-sequence modulated signal is observed with a temporal resolution of 10ps. We obtained a dynamic range of ∼40dB for the measurement bandwidth of 10 nm. When the measurement bandwidth is expanded to entire C-Band (∼35nm), the dynamic ranges of 37∼46dB were observed, depending on the wavelengths. The measurement time was sub-seconds throughout the experiment.

In an approximately synchronized (AS) code-division multiple-access (CDMA) communication system, zero correlation zone (ZCZ) sequences can be used as its spreading sequences so that the system suppresses multiple access interference (MAI) and multi-path interference (MPI) fully and synchronously. In this letter, the mutually orthogonal (MO) ZCZ polyphase sequence sets proposed by one of the authors are improved, and the resultant ZCZ sequences in each set arrive at the theoretical bound regarding ZCZ sequences under some conditions. Therefore, the improved MO ZCZ sequence sets are optimal.

In this paper, we consider the clustering problem of independent general subspaces. That is, with given data points lay near or on the union of independent low-dimensional linear subspaces, we aim to recover the subspaces and assign the corresponding label to each data point. To settle this problem, we take advantages of both greedy strategy and energy minimization strategy to propose a simple yet effective algorithm based on the assumption that an m-branched (i.e., perfect m-ary) tree which is constructed by collecting m-nearest neighbor points in each node has a high probability of containing the near-exact subspace. Specifically, at first, subspace candidates are enumerated by multiple m-branched trees. Each tree starts with a data point and grows by collecting nearest neighbors in the breadth-first search order. Then, subspace proposals are further selected from the enumeration to initialize the energy minimization algorithm. Eventually, both the proposals and the labeling result are finalized by iterative re-estimation and labeling. Experiments with both synthetic and real-world data show that the proposed method can outperform state-of-the-art methods and is practical in real application.

A Networked Control System (NCS) can be considered a form of Cyber-Physical System (CPS) with its network architecture and typical features, such as delay, jitter and package loss. So far, less discussion has been carried out for NCS from the view point of CPS. In this letter, the NCS with short delay is analyzed with cyber-physical integration. The sampling rate is depicted as one of the states in the state equations. The simulation results show that the cyber-physical integration not only adjusts the sampling rate to the states of the controlled physical system, but also adapts to the delay of the network. The averaged sampling rate and the stabilization time are smaller compared with the traditional NCS.

N-Shift Zero Correlation Zone (NS-ZCZ) sequence is defined with the N-shift zero correlation zone in the correlation function. Namely, the N-shift zero only appears within the correlation zone symmetrically distributed in the center of the correlation function. Moreover, the traditional ZCZ sequences can be considered as the N-shift ZCZ sequence with N=1. Similar to ZCZ sequence, NS-ZCZ sequences can be applied in sequence design for co-channel interference mitigation with more sequences in the sequence set compared with the traditional N-shift sequences. In this letter, the definition and construction algorithms are proposed. The corresponding theoretical bounds are analyzed.

Due to the fact that natural images are approximately sparse in Discrete Cosine Transform (DCT) or wavelet basis, the Compressive Sensing (CS) can be employed to decode both the host image and watermark with zero error, despite not knowing the host image. In this paper, Limited-Random Sequence (LRS) matrix is utilized to implement the blind CS detection, which benefits from zero error and lower complexity. The performance in Bit Error Rate (BER) and error-free detection probability confirms the validity and efficiency of the proposed scheme.

A highly integrated monolithic Multi-Service Transport Platform (MSTP) ASIC MSEOSX8-6 incorporating more than 26M transistors has been fabricated with 0.18 µm CMOS technology. The chip is a powerful monolithic MSTP ASIC that supports RPR applications and serves as a generic building block for MSTP network. To accelerate the chip design, we devise a novel methodology called Embedded Reduced Self-Tester (ERST), which integrates the reduced self-tester structure into the chip to shorten the duration of dynamic simulation. Moreover, we divide the design into 12 smaller Hierarchical Layout Blocks (HLB) to enable parallel layout. Resultantly, the whole design has been completed in 5 months, which saves at least 80% of the design cycle in all.

Orthogonal Signal Division Multiplexing (OSDM), also known as SD-OFDM, has been proposed for information transmission with high spectrum efficiency. In this paper, a new signal construction method named Adaptive Carrier Interferometry OSDM (ACI-OSDM) is proposed for time-frequency selective fading channel. Particularly, the Adaptive CI codes originated from CI-OFDM are employed in the frequency domain of OSDM signal. Compared with traditional OFDM, the ACI-OSDM improves the performance considerably of broadband transmission, i.e., spectrum efficiency, Peak-to-Average Power Ratio (PAPR) mitigation and interference cancelation in the high speed mobile environment with multipath emission, e.g. super express train with speed more than 250 km/h.

Tracking algorithms for arbitrary objects are widely researched in the field of computer vision. At the beginning, an initialized bounding box is given as the input. After that, the algorithms are required to track the objective in the later frames on-the-fly. Tracking-by-detection is one of the main research branches of online tracking. However, there still exist two issues in order to improve the performance. 1) The limited processing time requires the model to extract low-dimensional and discriminative features from the training samples. 2) The model is required to be able to balance both the prior and new objectives' appearance information in order to maintain the relocation ability and avoid the drifting problem. In this paper, we propose a real-time tracking algorithm called coupled randomness tracking (CRT) which focuses on dealing with these two issues. One randomness represents random projection, and the other randomness represents online random forests (ORFs). In CRT, the gray-scale feature is compressed by a sparse measurement matrix, and ORFs are used to train the sample sequence online. During the training procedure, we introduce a tree discarding strategy which helps the ORFs to adapt fast appearance changes caused by illumination, occlusion, etc. Our method can constantly adapt to the objective's latest appearance changes while keeping the prior appearance information. The experimental results show that our algorithm performs robustly with many publicly available benchmark videos and outperforms several state-of-the-art algorithms. Additionally, our algorithm can be easily utilized into a parallel program.

Multi-Carrier CDMA (MC-CDMA) has been considered as a combination of the techniques of Code Division Multiple Access (CDMA) and Orthogonal Frequency Division Multiplex (OFDM). However, even until now, the efficient MC-CDMA scheme is still under study because of the inherent bugs in OFDM, such as the troubles caused by Multiple Access Interference (MAI) and Peak to Average Power Ratio (PAPR). In this paper, we present a novel two-dimensional spreading sequence named "Two Dimensional Combined Complementary Sequence" (TDC). If we take this kind of sequences as spreading codes, several prominent advantages can be achieved compared with traditional MC-CDMA. First, it can achieve MAI free in the multi-path transmission both in uplink and downlink. Second, it offers low PAPR value within 3 dB with a quite simple architecture. The last but not the least, the proposed MC-CDMA scheme turns out to be an efficient approach with high bandwidth efficiency, high spreading efficiency and flexible transmission rate enriched by a special shift-and-add modulation. Meanwhile, an algorithm that constructs TDC sequences is discussed in details. Based on above results, we can get the conclusion that the novel TDC sequences and corresponding MC-CDMA architecture have great potential for applications in next generation wireless mobile communications, which require high transmission rate in hostile and complicated channels.

Compressive sensing enables quite lower sampling rate compared with Nyquist sampling. As long as the signal is sparsity in some basis, the random sampling with CS can be employed. In order to make CS applied in the practice, the Analog to Information Converter (AIC) should be involved. Based on the Limited Random Sequence (LRS) modulation, the AIC with LRS can be designed with high performance according to the fixed sparsity. However, if the sparsity of the signal varies with time, the original AIC with LRS is not efficient. In this paper, the adaptive AIC which adapts its scheme of LRS according to the variation of the sparsity is proposed and the prototype system is designed. Due to the adaption of the AIC with the scheme of LRS, the sampling rate can be further reduced. The simulation results confirm the performance of the proposed adaptive AIC scheme. The prototype system can successfully fulfil the random sampling and adapt to the variation of sparsity, which verify and consolidate the validity and feasibility for the future implementation of adaptive AIC on chip.

In this paper, we present a set of sequence pairs which produce zero correlation windows not only in the middle part of the sum of aperiodic correlation functions, but also in the two terminal parts. We name it "Ear Windows." In approximately synchronous CDMA communication system, this set of sequences is able to completely remove the inter-symbol interference (ISI) and multi-user interference (MUI) caused by the multi-path effect if the maximum delay is shorter than the length of the "Ear windows." In addition, it is also feasible in M-ary modulation. The inter-code interference will be mitigated drastically.