Optoelectronic technology is a new technology formed by the combination of photon technology and electronic technology. Photon technology can cause an industrial revolution that supersedes electronic technology, because it will have a deeper impact on industry and society. We review the development of optoelectronic devices and integration technologies. We compare and analyze the development and characteristics of optoelectronic technology platforms, summarize the key manufacturing technologies, introduce several representative optoelectronic devices including flexible devices, and focus on the key breakthrough technologies that need to be achieved. Through a comprehensive review of the development of optoelectronic technology, China should seize the opportunity for a transformation of the optoelectronic technology industry. By drawing on the experiences with advanced optoelectronic platforms and technologies in foreign countries, we should speed up the accumulation and reserves of Chinese industrial talents, pay attention to the accumulation of basic technology, and establish a national optoelectronic technology platform, to greatly enhance domestic levels in these regards and to achieve independent innovations with these devices.
Silicon photonics is a promising technology to address the demand for dense and integrated nextgeneration optical interconnections due to its complementary-metal-oxide-semiconductor (CMOS) compatibility. However, one of the key building blocks, the silicon modulator, suffers from several drawbacks, including a limited bandwidth, a relatively large footprint, and high power consumption. The graphene-based silicon modulator, which benefits from the excellent optical properties of the two-dimensional graphene material with its unique band structure, has significantly advanced the above critical figures of merit. In this work, we review the state-of-the-art graphenebased silicon modulators operating in various mechanisms, i.e., thermal-optical, electro-optical, and plasmonic. It is shown that graphene-based silicon modulators possess the potential to have satisfactory characteristics in intra- and inter-chip connections.
Heterogeneous III-V silicon (Si) photonic integration is considered one of the key methods for realizing power- and cost-effective optical interconnections, which are highly desired for future high-performance computers and datacenters. We review the recent progress in heterogeneous III-V/Si photonic integration, including transceiving devices and components. We also describe the progress in the on-wafer characterization of photonic integration circuits, especially on the heterogeneous III-V/Si platform.
We have summarized our recent work in the area of novel silica-based optical fibers, which can be classified into two types: silica optical fiber doped with special elements including Bi, Al, and Ce, and micro-structured multi-core fibers. For element-doped optical fiber, the Bi/Al co-doped silica fibers could exhibit a fluorescence spectrum covering the wavelength range between 1000 and 1400 nm with a full width at half maximum (FWHM) of about 150 nm, which enables its use in fiber amplifiers and laser systems. The Ce-doped fiber’s center wavelengths of excitation and emission are about 340 and 430 nm, respectively. The sapphire-derived fiber (SDF) with high alumina dopant concentration in the core can form mullite through heating and cooling with arc-discharge treatment. This SDF can be further developed for an intrinsic Fabry-Perot interferometric that can withstand 1200 °C, which allows it to be used in high-temperature sensing applications. Owing to the strong evanescent field, microstructured multi-core fiber can be used in a wide range of applications in biological fiber optic sensing, chemical measurement, and interference-related devices. Coaxial-core optical fiber is another novel kind of silica-based optical fiber that has two coaxial waveguide cores and can be used for optical trapping and micro-particle manipulation by generating a highly focused conical optical field. The recent developments of these novel fibers are discussed.
The design and fabrication of a compact and low-cost 4×25-Gb/s transmitter optical sub-assembly (TOSA) and receiver optical sub-assembly (ROSA) using a hybrid integrated technique are reported. TOSA and ROSA are developed without thermoelectric cooler for coarse wavelength division multiplexing applications. Physical dimension of the packaged optical subassembly is limited to 11.5 mm×5.4 mm×5.4 mm. The design of TOSA and ROSA is employed using a silica-based arrayed waveguide grating chip to select the specific channel wavelength at O-band. In TOSA, the wavelength of four 1.3-μm discrete directly modulated laser chips is well controlled based on the reconstruction equivalent chirp technique. In the back-to-back transmission test, bit error rates for all lanes of cascade of the TOSA and ROSA are small. A clear opening eye diagram is obtained.
A multimode silicon photonic integrated circuit (PIC) comprising a pair of on-chip mode (de)multiplexers with 10-mode channels and a multimode bus waveguide with sharp bends is demonstrated to enable multi-channel on-chip transmissions. The core width of the multimode bus waveguide is chosen such that it can support 10 guided modes, of which there are four transverse-magnetic polarization modes and six transverse-electric polarization modes. This multimode bus waveguide comprises sharp bends based on modified Euler curves. Experimental results demonstrate that the present silicon PIC enables the 10-channel on-chip transmission with a low inter-mode crosstalk of approximately −20 dB over a broad bandwidth of 1520–1610 nm even when the bending radius of the S-bend is as small as 40 μm. Compared with a silicon PIC using a conventional arc-bend with the same bending radius, our proposed PIC demonstrates a significant improvement.
Vector quantization (VQ) is a very effective way to save bandwidth and storage for speech coding and image coding. Traditional vector quantization methods can be divided into mainly seven types, tree-structured VQ, direct sum VQ, Cartesian product VQ, lattice VQ, classified VQ, feedback VQ, and fuzzy VQ, according to their codebook generation procedures. Over the past decade, quantization-based approximate nearest neighbor (ANN) search has been developing very fast and many methods have emerged for searching images with binary codes in the memory for large-scale datasets. Their most impressive characteristics are the use of multiple codebooks. This leads to the appearance of two kinds of codebook: the linear combination codebook and the joint codebook. This may be a trend for the future. However, these methods are just finding a balance among speed, accuracy, and memory consumption for ANN search, and sometimes one of these three suffers. So, finding a vector quantization method that can strike a balance between speed and accuracy and consume moderately sized memory, is still a problem requiring study.
Making rational decisions for sequential decision problems in complex environments has been challenging researchers in various fields for decades. Such problems consist of state transition dynamics, stochastic uncertainties, long-term utilities, and other factors that assemble high barriers including the curse of dimensionality. Recently, the state-of-the-art algorithms in reinforcement learning studies have been developed, providing a strong potential to efficiently break the barriers and make it possible to deal with complex and practical decision problems with decent performance. We propose a formulation of a velocity varying one-on-one quadrotor robot game problem in the threedimensional space and an approximate dynamic programming approach using a projected policy iteration method for learning the utilities of game states and improving motion policies. In addition, a simulation-based iterative scheme is employed to overcome the curse of dimensionality. Simulation results demonstrate that the proposed decision strategy can generate effective and efficient motion policies that can contend with the opponent quadrotor and gather advantaged status during the game. Flight experiments, which are conducted in the Networked Autonomous Vehicles (NAV) Lab at the Concordia University, have further validated the performance of the proposed decision strategy in the real-time environment.
Feature selection has attracted a great deal of interest over the past decades. By selecting meaningful feature subsets, the performance of learning algorithms can be effectively improved. Because label information is expensive to obtain, unsupervised feature selection methods are more widely used than the supervised ones. The key to unsupervised feature selection is to find features that effectively reflect the underlying data distribution. However, due to the inevitable redundancies and noise in a dataset, the intrinsic data distribution is not best revealed when using all features. To address this issue, we propose a novel unsupervised feature selection algorithm via joint local learning and group sparse regression (JLLGSR). JLLGSR incorporates local learning based clustering with group sparsity regularized regression in a single formulation, and seeks features that respect both the manifold structure and group sparse structure in the data space. An iterative optimization method is developed in which the weights finally converge on the important features and the selected features are able to improve the clustering results. Experiments on multiple real-world datasets (images, voices, and web pages) demonstrate the effectiveness of JLLGSR.
Control charts are commonly used tools in statistical process control for the detection of shifts in process parameters. Shewhart-type charts are efficient for large shift values, whereas cumulative sum (CUSUM) charts are effective in detecting medium and small shifts. Control chart use commonly assumes that data are free of outliers and parameters are known or correctly estimated based on an in-control process. In practice, these assumptions are not often true because some processes occasionally have outliers. Monitoring the location parameter is usually based on mean charts, which are seriously affected by violations of these assumptions. In this paper we propose several CUSUM median control charts based on auxiliary variables, and offer comparisons with their corresponding mean control charts. To monitor the location parameter, we examined the performance of mean and median control charts in the presence and absence of outliers. Both symmetric and non-symmetric processes were studied to examine the properties of the proposed control charts to monitor the location parameter using CUSUM control charts. We used different run length measures to study in-control and out-of-control performances of CUSUM charts. Results revealed that our proposed control charts perform much better than the traditional charts in the presence of outliers. A real application of our study was provided using data on concrete compressive strength as it relates to the quality of cement manufacturing.
Nonlinear oscillators and circuits can be coupled to reach synchronization and consensus. The occurrence of complete synchronization means that all oscillators can maintain the same amplitude and phase, and it is often detected between identical oscillators. However, phase synchronization means that the coupled oscillators just keep pace in oscillation even though the amplitude of each node could be different. For dimensionless dynamical systems and oscillators, the synchronization approach depends a great deal on the selection of coupling variable and type. For nonlinear circuits, a resistor is often used to bridge the connection between two or more circuits, so voltage coupling can be activated to generate feedback on the coupled circuits. In this paper, capacitor coupling is applied between two Pikovsk-Rabinovich (PR) circuits, and electric field coupling explains the potential mechanism for differential coupling. Then symmetric coupling and cross coupling are activated to detect synchronization stability, separately. It is found that resistor-based voltage coupling via a single variable can stabilize the synchronization, and the energy flow of the controller is decreased when synchronization is realized. Furthermore, by applying appropriate intensity for the coupling capacitor, synchronization is also reached and the energy flow across the coupling capacitor is helpful in regulating the dynamical behaviors of coupled circuits, which are supported by a continuous energy exchange between capacitors and the inductor. It is also confirmed that the realization of synchronization is dependent on the selection of a coupling channel. The approach and stability of complete synchronization depend on symmetric coupling, which is activated between the same variables. Cross coupling between different variables just triggers phase synchronization. The capacitor coupling can avoid energy consumption for the case with resistor coupling, and it can also enhance the energy exchange between two coupled circuits.
We propose a modified Fitzhugh-Nagumo neuron (MFNN) model. Based on this model, an integerorder MFNN system (case A) and a fractional-order MFNN system (case B) were investigated. In the presence of electromagnetic induction and radiation, memductance and induction can show a variety of distributions. Fractionalorder magnetic flux can then be considered. Indeed, a fractional-order setting can be acceptable for non-uniform diffusion. In the case of an MFNN system with integer-order discontinuous magnetic flux, the system has chaotic and non-chaotic attractors. Dynamical analysis of the system shows the birth and death of period doubling, which is a sign of antimonotonicity. Such a behavior has not been studied previously in the dynamics of neurons. In an MFNN system with fractional-order discontinuous magnetic flux, different attractors such as chaotic and periodic attractors can be observed. However, there is no sign of antimonotonicity.