Global asymptotic stability for Hopfield-type neural networks with diffusion effects

The existence, uniqueness and global asymptotic stability for the equilibrium of Hopfield-type neural networks with diffusion effects are studied. When the activation functions are monotonously nondecreasing, differentiable, and the interconnected matrix is related to the Lyapunov diagonal stable matrix, the sufficient conditions guaranteeing the existence of the equilibrium of the system are obtained by applying the topological degree theory. By means of constructing the suitable average Lyapunov functions, the global asymptotic stability of the equilibrium of the system is also investigated. It is shown that the equilibrium （if it exists） is globally asymptotically stable and this implies that the equilibrium of the system is unique.

Existence of Periodic Solutions for Neutral-Type Neural Networks with Delays on Time Scales

In this paper, we employ a fixed point theorem due to Krasnosel’skii to attain the existence of periodic solutions for neutral-type neural networks with delays on a periodic time scale. Some new sufficient conditions are established to show that there exists a unique periodic solution by the contraction mapping principle.

Monthly Mean Temperature Prediction Based on a Multi－level Mapping Model of Neural Network BP Type

In terms of 34-year monthly mean temperature series in 1946-1979,the multi-level maPPing model of neural netWork BP type was applied to calculate the system's fractual dimension Do=2'8,leading tO a three-level model of this type with ixj=3x2,k=l,and the 1980 monthly mean temperture predichon on a long-t6rm basis were prepared by steadily modifying the weighting coefficient,making for the correlation coefficient of 97% with the measurements.Furthermore,the weighhng parameter was modified for each month of 1980 by means of observations,therefore constrcuhng monthly mean temperature forecasts from January to December of the year,reaching the correlation of 99.9% with the measurements.Likewise,the resulting 1981 monthly predictions on a long-range basis with 1946-1980 corresponding records yielded the correlahon of 98% and the month-tO month forecasts of 99.4%.

Parameter Optimization of Interval Type-2 Fuzzy Neural Networks Based on PSO and BBBC Methods

Interval type-2 fuzzy neural networks(IT2FNNs)can be seen as the hybridization of interval type-2 fuzzy systems(IT2FSs) and neural networks(NNs). Thus, they naturally inherit the merits of both IT2 FSs and NNs. Although IT2 FNNs have more advantages in processing uncertain, incomplete, or imprecise information compared to their type-1 counterparts, a large number of parameters need to be tuned in the IT2 FNNs,which increases the difficulties of their design. In this paper,big bang-big crunch(BBBC) optimization and particle swarm optimization(PSO) are applied in the parameter optimization for Takagi-Sugeno-Kang(TSK) type IT2 FNNs. The employment of the BBBC and PSO strategies can eliminate the need of backpropagation computation. The computing problem is converted to a simple feed-forward IT2 FNNs learning. The adoption of the BBBC or the PSO will not only simplify the design of the IT2 FNNs, but will also increase identification accuracy when compared with present methods. The proposed optimization based strategies are tested with three types of interval type-2 fuzzy membership functions(IT2FMFs) and deployed on three typical identification models. Simulation results certify the effectiveness of the proposed parameter optimization methods for the IT2 FNNs.

Periodic Solution for Neutral Type Neural Networks

The principle aim of this paper is to explore the existence of periodic solution of neural networks model with neutral delay. Sufficient and realistic conditions are obtained by means of an abstract continuous theorem of k-set contractive operator and some analysis technique.

Multistability of delayed complex-valued recurrent neural networks with discontinuous real-imaginarytype activation functions

In this paper, the multistability issue is discussed for delayed complex-valued recurrent neural networks with discontinuous real-imaginary-type activation functions. Based on a fixed theorem and stability definition, sufficient criteria are established for the existence and stability of multiple equilibria of complex-valued recurrent neural networks. The number of stable equilibria is larger than that of real-valued recurrent neural networks, which can be used to achieve high-capacity associative memories. One numerical example is provided to show the effectiveness and superiority of the presented results.

Cohen-Grossberg-type BAM神经网络吸引集和不变集(英文)

利用矩阵理论和不等式分析技巧,讨论了一类具分布时滞的Cohen-Grossberg型BAM神经网络的不变集和吸引集,获得了一些最新结果,并给出一个实例说明我们结果的可行性.

Synthesization of high-capacity auto-associative memories using complex-valued neural networks

In this paper, a novel design procedure is proposed for synthesizing high-capacity auto-associative memories based on complex-valued neural networks with real-imaginary-type activation functions and constant delays. Stability criteria dependent on external inputs of neural networks are derived. The designed networks can retrieve the stored patterns by external inputs rather than initial conditions. The derivation can memorize the desired patterns with lower-dimensional neural networks than real-valued neural networks, and eliminate spurious equilibria of complex-valued neural networks. One numerical example is provided to show the effectiveness and superiority of the presented results.

Nerve growth factor and inducible nitric oxide synthase expression in the mesencephalon and diencephalon, as well as visual-and auditory-related nervous tissues, in a macaque model of type 2 diabetes

The present study detected distribution and expression of nerve growth factor and inducible nitric oxide synthase in the mesencephalon and diencephalon, as well as visual- and auditory-related nervous tissues, in a macaque model of type 2 diabetes using immunohistochemistry. Results showed that nerve growth factor expression decreased, but inducible nitric oxide synthase expression increased, in the mesencephalon and diencephalon, as well as visual- and auditory- related nervous tissues. These results suggested that nerve growth factor and inducible nitric oxide synthase play an important role in regulating the development of diabetic visual- and auditory-related diseases.

Analysis and Control of Novel Deflection-Type PM Multi-DOF Actuator

This paper mainly presents a PM multi-DOF actuator for robot in-wheels drive applications and its control method. The torque model is established based on the finite-element model of the single pair poles in 3D finite element method software. Due to the special structure of the actuator,the Euler angles are adopted for deriving the kinematics and dynamic model. To reduce the effects of uncertainties of modeling error,nonlinear friction and external disturbances in the system,an approximation of neural network adaptive control method is applied to the actuator. The computation and simulation results show that the proposed analysis and control method can effectively derive the characteristics and improve the motion performance,which provides the primary theoretical guide for the configuration design,optimization and control research of multi-DOF deflection type actuators.

HLA class Ⅱ alleles and risk for peripheral neuropathy in type 2 diabetes patients

The potential impact of human leukocyte antigen （HLA） genotype variations on development of diabetic peripheral neuropathy （DPN） is not well determined. This study aimed to identify the association of HLA class II alleles with DPN in type 2 diabetes （T2D） patients. Totally 106 T2D patients, 49 with DPN and 57 without DPN, and 100 ethnic-matched healthy controls were analyzed. Both groups of the patients were matched based on sex, age, body mass index （BMI） and duration of T2D. Polyneuropathy was diagnosed using electrodiagnostic methods. HLA-DRB1 and DQB1 genotyping was performed in all subjects by the polymerase chain reaction with sequence-specific primers （PCR-SSP） method. T2D patients with DPN showed higher frequencies of HLA-DRB1＊10 and DRB1＊12 alleles compared to control group （P = 0.04）. HLA-DQB1＊02 allele and HLA-DRB1＊07-DQB1＊02 haplotype were associated with a decreased risk for developing DPN in T2D patients （P = 0.02 and P = 0.05 respectively）. Also, patients with severe neuropathy showed higher frequencies of DRB1＊07 （P = 0.003） and DQB1＊02 （P = 0.02） alleles than those with mild-to-moderate form of neuropathy. The distribution of DRB 1 and DQB 1 alleles and haplotypes were not statistically different between all patients and healthy controls. Our findings implicate a possible protective role of HLA-DQB1＊02 allele and HLA-DRB1＊07-DQB1＊02 haplotype against development of peripheral neuropathy in T2D patients. Therefore, variations in HLA genotypes might be used as genetic markers for prediction and potentially management of neuropathy in T2D patients.

T-type calcium channel expression in cultured human neuroblastoma cells

Human neuroblastoma cells （SH-SY5Y） have similar structures and functions as neural cells and have been frequently used for cell culture studies of neural cell functions.Previous studies have revealed L-and N-type calcium channels in SH-SY5Y cells.However,the distribution of the low-voltage activated calcium channel （namely called T-type calcium channel,including Cav3.1,Cav3.2,and Cav3.3） in SH-SY5Y cells remains poorly understood.The present study detected mRNA and protein expres-sion of the T-type calcium channel （Cav3.1,Cav3.2,and Cav3.3） in cultured SH-SY5Y cells using real-time polymerase chain reaction （PCR） and western blot analysis.Results revealed mRNA and protein expression from all three T-type calcium channel subtypes in SH-SY5Y cells.Moreover,Cav3.1 was the predominant T-type calcium channel subtype in SH-SY5Y cells.

Changes in proprotein convertase subtilisin/kexin type 9 mRNA expression in rat cortex after cerebral ischemia

Oxidized low density lipoprotein is a risk factor for cerebrovascular disease. Proprotein convertase subtilisin/kexin type 9 （PCSK9） can increase the level of low density lipoprotein. Therefore, this study assumed that PCSK9 plays important roles in ischemic cerebrovascular disease. The present study established transient focal cerebral ischemia models after 100 minutes of middle cerebral artery occlusion. In situ hybridization demonstrated that PCSK9 mRNA expression increased gradually with prolonged reperfusion time in ischemic cortices. This indicated that transient focal cerebral ischemia upregulated PCSK9 mRNA expression in ischemic cortices.

Effect of glycosides of Cistanche on the expression of mitochondrial precursor protein and keratin type Ⅱ cytoskeletal 6A in a rat model of vascular dementia

Glycosides of Cistanche（GC）is a preparation used extensively for its neuroprotective effect against neurological diseases,but its mechanisms of action remains incompletely understood.Here,we established a bilateral common carotid artery occlusion model of vascular dementia in rats and injected the model rats with a suspension of GC（10 mg/kg/day,intraperitoneally）for 14 consecutive days.Immunohistochemistry showed that GC significantly reduced p-tau and amyloid beta（Aβ）immunoreactivity in the hippocampus of the model rats.Proteomic analysis demonstrated upregulation of mitochondrial precursor protein and downregulation of keratin type II cytoskeletal6A after GC treatment compared with model rats that had received saline.Western blot assay confirmed these findings.Our results suggest that the neuroprotective effect of GC in vascular dementia occurs via the promotion of neuronal cytoskeleton regeneration.

基于BP神经网络的重力仪高机动状态快速调平修正技术

针对平台式重力仪大机动状态后测量能力恢复慢的问题,提出一种基于BP神经网络的重力仪稳定平台快速调平修正技术。首先,针对动态重力测量在测量平台大机动状态后调平能力不足的问题,研究了基于BP神经网络的平台姿态高效、准确解算方法;其次,利用惯性元件和卫星导航系统(GNSS)的信息优化BP神经网络,形成不同条件的平台姿态提取优化模型;最后,利用模拟仿真实验和实际机载动态重力测量数据验证所提方法的有效性和准确性。实验结果表明在大机动的动态条件下采用所提方法可以扶正重力仪稳定平台,将机动后重力仪稳定平台稳定时间缩短83.3%以上,提升动态重力测量效率。

Neurons in the hippocampal CA1 region,but not the dentate gyrus,are susceptible to oxidative stress in rats with streptozotocin-induced type 1 diabetes

In this study, we investigated the effects of streptozotocin-induced type 1 diabetes on antioxi- dant-like protein-1 immunoreactivity, protein carbonyl levels, and malondialdehyde formation, a marker for lipid peroxidation, in the hippocampus. For this study, streptozotocin （75 mg/kg） was intraperitoneally injected into adult rats to induce type 1 diabetes. The three experimental pa- rameters were determined at 2, 3, 4 weeks after streptozotocin treatment. Fasting blood glucose levels significantly increased by 20.7-21.9 mM after streptozotocin treatment. The number of antioxidant-like protein-1 immunoreactive neurons significantly decreased in the hippocampal CA1 region, but not the dentate gyrus, 3 weeks after streptozotocin treatment compared to the control group. Malondialdehyde and protein carbonyl levels, which are modified by oxidative stress, significantly increased with a peak at 3 weeks after malondialdehyde treatment, and then decreased 4 weeks after malondialdehyde treatment. These results suggest that neurons in the hippocampal CA1 region, but not the dentate gyrus, are susceptible to oxidative stress 3 weeks after malondialdehyde treatment.

基于依赖类型剪枝的双特征自适应融合网络用于方面级情感分析

现有的模型将基于依赖树的图神经网络用于方面级情感分析,一定程度上提升了模型的分类性能。然而,由于依赖解析技术的限制,语法解析结果的不精确导致依赖树存在大量噪声,使得模型的性能提升有限。此外,一些句子本身并不符合标准的句法结构。以往的研究以同样的置信度利用句法信息和语义信息,没有充分考虑它们对于确定方面词极性的贡献的不同,导致模型在相应的数据集上性能较差。为了克服这些困难,文中提出了一种基于依赖类型剪枝的双特征自适应融合网络。具体来说,该模型使用一种新型的混合方法,命名为依赖关系类型剪枝和邻接矩阵平滑,来缓解句法解析产生的噪声。此外,该模型通过双特征自适应融合模块充分考虑句子的句法信息的可用程度,以一种更灵活的方式将句法特征和语义特征结合起来用于方面级情感分析。在5个公开可用的数据集上进行广泛的实验,结果证明了该方法明显优于基线模型。