Arbitrary Coding Research Articles

Metasurfaces enabled dual-wavelength decoupling of near-field and far-field encoding

The metasurface is a platform with a small footprint and abundant functionalities. With propagation phase and geometric phase, polarization multiplexing is possible. However, different response behaviors of propagation phase and geometric phase to wavelength have not been fully employed to widen the capabilities of metasurfaces. Here, we theoretically demonstrate that metasurfaces can achieve near-field and far-field decoupling with the same polarization at two wavelengths. First, we found a set of pillars whose propagation phase difference between two wavelengths covers the full range of 2π. Then, by rotating pillars to control the geometric phase, the phase at both wavelengths can cover the full range of 2π. Finally, by means of interference principle, arbitrary independent coding for the near field and far field of dual wavelengths is realized. In addition, when the far-field function is focusing, the focused spot is close to the diffraction limit, and, when the NA of the lens is very small, the final output focal length is four times of initial input focal length. This work circumvents the strong wavelength-dependent limitation of planar devices and paves the way toward designing multi-wavelength and multi-functional metadevices for scenarios such as AR applications, fluorescence microscopy, and stimulated emission depletion microscopy.

Dynamic beam all-direlectric coding metasurface converter based on phase change materials of GST

Phase change materials, especially Ge2Sb2Te5(GST), play an important role in the design of dynamic all-dielectric metasurface due to its flexibility and adjustability. And its non-volatility makes it possible to form dynamic metasurfaces with complex functions. In this paper, we propose a cross-shaped all-dielectric metasurface based on GST interlayer, which can achieve ultra-high transmittance and complete 2π phase coverage in the near-infrared band when the interlayer material is in amorphous state. Through multipole decomposition and field distribution characterization, we have revealed the regulation principles of the unit cell before and after the switching. And thus, we designed the arrays of metasurface with switchable beam deflection, arbitrary coding and focusing functions. Holographic reconstruction based on GS algorithm is discussed and extended to independent control of the RGB channels in imaging applications. Our research can provide a reference for the design of compact multifunctional optical elements, optical encryption and dynamic metasurfaces.

An optically transparent unequal proportional coding metasurface with absorption and diffusion integrated mechanism for ultra-broadband RCS reduction

In this paper, a novel uneven layered transparent absorption-diffusion integrated coding metamaterials is proposed to suppress the ultra-broadband backward scattering within a wide angular domain. The metasurface achieves RCS reduction through the combined action of scattering and absorption mechanisms. The two different units of this metasurface exhibit a reflection phase difference of 180 ± 37° covering from 3.1 to 17.1 GHz with various amplitudes for both the morphology of the units and the location on the different planes. Additionally, an unequal proportional design of the coding metasurface is applied to further enhance the diffusion of the backward scattering wave at a specific frequency. Then, the arbitrary coding sequence of the units is optimized using the particle swarm optimization (PSO) algorithm to obtain the optimal arrangement of the units. This novel coding metasurface can achieve a wide-angle low-scattering characteristic from 0° to 50° for transverse electric (TE) and transverse magnetic (TM) polarizations, demonstrating a considerable potential for future microwave absorbing and shielding glasses applications.

Storage capacity of networks with discrete synapses and sparsely encoded memories.

Attractor neural networks are one of the leading theoretical frameworks for the formation and retrieval of memories in networks of biological neurons. In this framework, a pattern imposed by external inputs to the network is said to be learned when this pattern becomes a fixed point attractor of the network dynamics. The storage capacity is the maximum number of patterns that can be learned by the network. In this paper, we study the storage capacity of fully connected and sparsely connected networks with a binarized Hebbian rule, for arbitrary coding levels. Our results show that a network with discrete synapses has a similar storage capacity as the model with continuous synapses, and that this capacity tends asymptotically towards the optimal capacity, in the space of all possible binary connectivity matrices, in the sparse coding limit. We also derive finite coding level corrections for the asymptotic solution in the sparse coding limit. The result indicates the capacity of networks with Hebbian learning rules converges to the optimal capacity extremely slowly when the coding level becomes small. Our results also show that in networks with sparse binary connectivity matrices, the information capacity per synapse is larger than in the fully connected case, and thus such networks store information more efficiently.

On the Design of Channel Coding Autoencoders With Arbitrary Rates for ISI Channels

This letter presents an autoencoder-based channel coding scheme in the presence of inter-symbol interference (ISI) and additive white Gaussian noise (AWGN), supporting arbitrary coding rates. Both the transmitter and receiver of the proposed autoencoder employ bi-directional gated recurrent unit (Bi-GRU) layers. Additional extra dense layers are applied at the end of the transmitter and at the beginning of the receiver, serving as learnable puncture and depuncture modules, respectively. Different code rates can be achieved by adjusting the output dimension of the extra dense layers. Experimental results demonstrate that the proposed autoencoder significantly outperforms conventional convolutional codes over ISI channels, for multiple code rates. The proposed autoencoder also outperforms LDPC codes in the low signal-to-noise ratio (SNR) regime. The neural codes still require improvement to be competitive in the high SNR regime.

High-performance ultra-broadband absorption–diffusion integrated metasurface

We propose an absorption–diffusion integrated metasurface that achieves high-performance stealth of electromagnetic waves with high angular stability in an ultrabroad frequency band. To this end, we designed two types of absorbing meta-atoms with reflection coefficients less than −10 dB in the broadband, which can maintain a phase difference of ∼180° in the range of 5.35–13.5 GHz. Then, the genetic algorithm is utilized to optimize the relationship between the arbitrary coding sequence of meta-atoms and their far-field patterns to obtain the optimal arrangement of the meta-atoms of the metasurface. The simulation and test results of the sample show that the polarization-independent radar cross section (RCS) reduction characteristic over −10 dB in the broadband range (4–18 GHz in simulation and 4.8–16.8 GHz in test) can be achieved. Particularly, the proposed metasurface achieves RCS reduction values over −30 dB in the 7.7–12.4 GHz range. At the same time, the RCS reduction behavior of −10 dB can be maintained to 45° oblique incidence. Experiment and simulation results demonstrate the effectiveness of the present scheme, and the proposed metasurface exhibits better RCS reduction performance than other published literature. This work is of great significance for the rapid design of high-performance absorption–diffusion integrated metasurfaces, which have important prospects in stealth, camouflage, and other related applications.

Epigenetics and Bruxism: from Hyper-Narrative Neural Networks to Hyper-Function

This article develops a biosemiotic ´hyper-narrative model´ for the purposes of investigating emergent motor behaviors. It proposes to understand such behaviors in terms of the following associations: the organization of information acquired from the environment, focusing on narrative; the organizational dynamics of epigenetic mechanisms that underly the neural processes facilitating the processing of information; and the evolution of emergent motor behaviors that enable the informational acquisition. The article describes and explains these associations as part of a multi-ordered and multi-causal generative principle of biological phenotype emergence that supersedes the theory of the arbitrary coding of life. Preceeding from narrative’s operations in a biological dimension, the article presents scientific research dealing with the associations of action-oriented organization of narrative information and underlying psychological and physiological dynamics and depicts the relations with a distributed multi-directional mapping dynamic. The article presents the explanatory implications of such a hyper-narrative dynamic model on an example of emergent motor behaviors – bruxism. Central to this discussion is the exploration of the possible mechanisms of emergence and etiopathogenesis of bruxism, based on its neurobiology. The article takes the perspective that complex systems dynamics themselves with a tendency to narrative form are found not to be underlain merely by arbitrary coded mechanisms but, rather, biological neural networks (e.g. neuro-epigenetic network) that render context-dependent bio-informational mapping analogous to that of the narrative possible.

Absorptive coding metasurface for further radar cross section reduction

Lossless coding metasurfaces and metamaterial absorbers have been widely used for radar cross section (RCS) reduction and stealth applications, which merely depend on redirecting electromagnetic wave energy into various oblique angles or absorbing electromagnetic energy, respectively. Here, an absorptive coding metasurface capable of both the flexible manipulation of backward scattering and further wideband bistatic RCS reduction is proposed. The original idea is carried out by utilizing absorptive elements, such as metamaterial absorbers, to establish a coding metasurface. We establish an analytical connection between an arbitrary absorptive coding metasurface arrangement of both the amplitude and phase and its far-field pattern. Then, as an example, an absorptive coding metasurface is demonstrated as a nonperiodic metamaterial absorber, which indicates an expected better performance of RCS reduction than the traditional lossless coding metasurface and periodic metamaterial-absorber. Both theoretical analysis and full-wave simulation results show good accordance with the experiment.

Background pretruncated method for JPEG2000 region of interest coding

We propose a new method for JPEG2000 region of interest (ROI) coding called the background pretruncated method (BPTM). An algorithm to calculate the key parameter in the BPTM is also proposed. The published JPEG2000 ROI coding methods have difficulty in balancing ROI quality and system computation. Methods based on shifting coefficients add much computation, and they significantly penalize the coding efficiency. Implicit methods cannot obtain as high-ROI quality as the coefficient shift methods. To efficiently achieve ROI coding, the BPTM assigns a proper number of the least significant bitplanes of the background to zero, and it can not only achieve high-ROI quality but also add no computation to the other modules in JPEG2000. Additionally, the BPTM supports arbitrary shaped ROI coding, and the codestream is compatible with JPEG2000 standard.

Generalized resolution for orthogonal arrays

The generalized word length pattern of an orthogonal array allows a ranking of orthogonal arrays in terms of the generalized minimum aberration criterion (Xu and Wu [Ann. Statist. 29 (2001) 1066-1077]). We provide a statistical interpretation for the number of shortest words of an orthogonal array in terms of sums of $R^2$ values (based on orthogonal coding) or sums of squared canonical correlations (based on arbitrary coding). Directly related to these results, we derive two versions of generalized resolution for qualitative factors, both of which are generalizations of the generalized resolution by Deng and Tang [Statist. Sinica 9 (1999) 1071-1082] and Tang and Deng [Ann. Statist. 27 (1999) 1914-1926]. We provide a sufficient condition for one of these to attain its upper bound, and we provide explicit upper bounds for two classes of symmetric designs. Factor-wise generalized resolution values provide useful additional detail.

Bounds on the Benefit of Network Coding for Wireless Multicast and Unicast

In this paper, we explore fundamental limitations of the benefit of network coding in multihop wireless networks. We study two well-accepted scenarios in the field: single multicast session and multiple unicast sessions. We assume arbitrary but fixed topology and traffic patterns for the wireless network. We prove that the gain of network coding in terms of throughput and energy saving of a single multicast session is at most a constant factor. Also, we present a lower bound on the average number of transmissions of multiple unicast sessions under any arbitrary network coding. We identify scenarios under which network coding provides no gain at all, in the sense that there exists a simple flow scheme that achieves the same performance. Moreover, we prove that the gain of network coding in terms of the maximum transport capacity is bounded by a constant factor of at most $(\pi)$ in any arbitrary wireless network under all traditional Gaussian channel models. As a corollary, we find that the gain of network coding on the throughput of large homogeneous wireless networks is asymptotically bounded by a constant. Furthermore, we establish theorems which relate a network coding scheme to a simple routing scheme for multiple unicast sessions. The theorems can be used as criteria for evaluating the potential gain of network coding in a given wired or wireless network. Based on these criteria, we find more scenarios where network coding has no gain on throughput or energy saving.

On Convexity of Error Rates in Digital Communications

Convexity properties of error rates of a class of decoders, including the ML/min-distance one as a special case, are studied for arbitrary constellations, bit mapping and coding. Earlier results obtained for the AWGN channel are extended to a wide class of noise densities, including unimodal and spherically-invariant noise. Under these broad conditions, symbol and bit error rates are shown to be convex functions of the SNR in the high-SNR regime with an explicitly-determined threshold, which depends only on the constellation dimensionality and minimum distance, thus enabling an application of the powerful tools of convex optimization to such digital communication systems in a rigorous way. It is the decreasing nature of the noise power density around the decision region boundaries that insures the convexity of symbol error rates in the general case. The known high/low SNR bounds of the convexity/concavity regions are tightened and no further improvement is shown to be possible in general. The high SNR bound fits closely into the channel coding theorem: all codes, including capacity-achieving ones, whose decision regions include the hardened noise spheres (from the noise sphere hardening argument in the channel coding theorem) satisfies this high SNR requirement and thus has convex error rates in both SNR and noise power. We conjecture that all capacity-achieving codes have convex error rates. Convexity properties in signal amplitude and noise power are also investigated. Some applications of the results are discussed. In particular, it is shown that fading is convexity-preserving and is never good in low dimensions under spherically-invariant noise, which may also include any linear diversity combining.

Cooperative Performance and Diversity Gain of Wireless Relay Networks

In this paper, the error rate performance and diversity gain of amplify-and-forward (AF) wireless relay networks are studied. The distributed space-time block code (DSTBC) in a synchronous relay network with multiple relay nodes is considered. The distributed linear dispersion code is used at the relays. The symbol (or codeword) error rate is studied in terms of upper and lower bounds through rigorous derivations, and the diversity gain of the DSTBC is derived, for any number of relay nodes. As a corollary, a necessary and sufficient condition is obtained for achieving full cooperative diversity. Arbitrary coding matrices at the relays, path loss and general linear power allocation are considered. Finally, the orthogonal frequency division multiplexing (OFDM)-based space-time transmission scheme in asynchronous cooperative networks is also discussed.

Multi-Dimensional Graph-Based Soft Iterative Receiver for MIMO-OFDM

A graph-based receiver is presented that iteratively performs soft channel estimation and soft data detection. Reliability information of data symbols is utilized to improve channel estimation, and in turn, soft channel estimates refine data symbol estimates. The proposed multi-dimensional factor graph introduces transfer nodes that exploit correlation of adjacent channel coefficients in an arbitrary number of dimensions (e.g. time, frequency, and spatial domain). This establishes a simple and flexible receiver structure that facilitate soft channel estimation and data detection in multi-dimensional dispersive channels, and supports arbitrary modulation and channel coding schemes. Simulation results demonstrate that the proposed multi-dimensional graph-based receiver outperforms iterative and non-iterative state-of-the-art receivers.

A New Diagnosis Loseless Compression Method for Digital Mammography Based on Multiple Arbitrary Shape ROIs Coding Framework

With the rapidly growing use of digital images in medical archival and communication, image compression technology, especially diagnosis lossless compression technology, plays a more and more important role for medical applications. In this thesis, a novel diagnosis loseless compression algorithm is presented for digital mammography. The mammogram is divided into breast region, pectoral muscle and background using the CAD technology. Then mutiple arbitrary shape ROIs coding framework is used to compress the mammogram in which the breast region and pectoral muscle are compressed losslessly and lossily respectively, and the background can be discarded or compressed lossily as user's will. Experimental results show that the proposed method offer potential advantage in medical applications of digital mammography compression.

Arbitrary ROI-based wavelet video coding

This paper presents a novel arbitrary shape region of interest (ROI) coding for scalable wavelet video codec. The motion information of the ROIs is estimated by macroblock padding and polygon matching. The derived motion vectors are set as the motion trajectory of the samples to generate a one-dimensional temporal signal. This signal is then filtered to reduce the temporal redundancy using motion compensated temporal filtering for arbitrary shape ROI. Compared to traditional non-ROI coding, the reconstructed quality of the ROI coding can be significantly improved at low bit-rates. The efficiency of motion compensated temporal filtering (MCTF) based on arbitrary ROI is also compared with that of the video object coding in MPEG-4. Based on large number of experiments, the ability of the MCTF to reduce the temporal redundancy is demonstrated as better than (or at least comparable to) that of MPEG-4.

Joint Coding/Routing Optimization for Distributed Video Sources in Wireless Visual Sensor Networks

This paper studies a joint coding/routing optimization between network lifetime and video distortion by applying information theory to wireless visual sensor networks for correlated sources. Arbitrary coding [distributed video coding and network coding (NC)] from both combinatorial optimization and information theory could make significant progress toward the performance limit and tractable. Also, multipath routing can spread energy utilization across nodes within the entire network to keep a potentially longer lifetime, and solve the wireless contention issues by the splitting traffic. The objective function not only keeps the total energy consumption of encoding power, transmission power, and reception power minimized, but ensures the information received by sink nodes to approximately reconstruct the visual field. Also, a generalized power consumption model for distributed video sources is developed, in which the coding complexity of Key frames and Wyner-Ziv frames is measured by translating specific coding behavior into energy consumption. On the basis of the distributed multiview video coding and NC-based multipath routing, the balance problem between lifetime (costs) and distortion (capacity) is modeled as an optimization formulation with a fully distributed solution. Through a primal decomposition, a two-level optimization is relaxed with Lagrangian dualization and solved by the gradient algorithm. The low-level optimization problem is further decomposed into a secondary master dual problem with four cross-layer subproblems: a rate control problem, a channel contention problem, a distortion control problem, and an energy conservation problem. The implementation of the distributed algorithm is discussed with regard to the communication overhead and dynamic network change. Simulation results validate the convergence and performance of the proposed algorithm.

Tunable Lattice-Form Mach–Zehnder Interferometer for Arbitrary Binary Code Generation at 40 GHz

We use the direct temporal domain approach to design spectrally periodic optical filters for pulse repetition rate multiplication (PRRM) with envelope shaping. In particular, we demonstrate a tunable lattice-form Mach-Zehnder interferometer using Silica-based planar lightwave circuit (PLC) for arbitrary 4-bit binary amplitude code generation at 40 GHz and to increase the repetition rate of a 10 GHz input pulse train to 20 GHz or 40 GHz. In addition to PRRM and envelope shaping, the device also has the capability of arbitrary phase coding.

Reducing control selection errors associated with underground bolting equipment

Selecting the incorrect control during the operation of underground bolting and drilling equipment causes serious injuries. Shape coding and the layout of dual control banks are two aspects of control design which require further examination. The aims of this research were: (i) to determine whether arbitrary shape coding was effective in reducing selection error rates in a virtual analogy of roof-bolting; and (ii) to determine whether any advantages exist for mirror or place layouts for dual control situations in this situation. Two experiments were conducted to address these questions. No benefits of arbitrary shape coding were evident while control location remained constant. When control location was altered, shape coding did provide a significant reduction in selection error rate. No differences between mirror or place arrangements were detected and this question remains open.

Real-time Chirp-Coded Imaging With a Programmable Ultrasound Biomicroscope

Ultrasound biomicroscopy (UBM) of mice can provide a testing ground for new imaging strategies. The UBM system presented in this paper facilitates the development of imaging and measurement methods with programmable design, arbitrary waveform coding, broad bandwidth (2-80 MHz), digital filtering, programmable processing, RF data acquisition, multithread/multicore real-time display, and rapid mechanical scanning (<or=170 frames/s). To demonstrate the capacities of the UBM system, chirp (1.28, 2.56, and 5.12 micros durations) sequences with matched filter analysis are implemented in real time. Chirp and conventional impulse imaging (31 and 46 MHz center frequencies) of a wire phantom at fast sectorial scanning (0.7 degrees ms(-1), 20 frames/s one-way image rate) are compared. Axial and lateral resolutions at the focus with chirps approach impulse imaging resolutions. Chirps yield 10-15 dB gain in SNR and a 2-3 mm gain in imaging depth. Real-time impulse and chirp-coded imaging (at 10-5 frames/s) are demonstrated in the mouse, in vivo. The system's open structure favors test and implementation of new sequences.