In this paper, the event-triggered state estimation problem is investigated for a class of discrete-time multidelayed neural networks with stochastic parameters and incomplete measurements. order to cater more realistic transmission process signals, we make first attempt introduce set variables characterize random fluctuations system parameters. addressed network model, delays among interconnections are allowed be different, which general than those in existing literature. The information...

Abstract Traditional joint-link robots have been widely used in production lines because of their high precision for single tasks. With the development manufacturing and service industries, requirement comprehensive performance robotics is growing. Numerous types bio-inspired investigated to realize human-like motion control manipulation. A study route from inner mechanisms external structures proposed imitate humans animals better. this idea, a brain-inspired intelligent robotic system...

In this paper, we investigate the stochastic stabilization problem for a class of bilinear continuous time-delay uncertain systems with Markovian jumping parameters. Specifically, jump system under study involves unknown state time-delay, parameter uncertainties, and nonlinear deterministic disturbances. The parameters considered here form continuous-time discrete-state homogeneous Markov process. whole may be regarded as hybrid that includes both time-evolving event-driven mechanisms. Our...

Recently, we have provided evidence that the polymorphic self-incompatibility (S) locus-encoded F-box (SLF) protein AhSLF-S2 plays a role in mediating selective S-RNase destruction during self-incompatible response Antirrhinum hispanicum. To investigate its further, first transformed transformation-competent artificial chromosome clone (TAC26) containing both and AhS2-RNase into (SI) line of Petunia hybrida. Molecular analyses showed genes are correctly expressed pollen pistil four...

Self-incompatibility S-locus–encoded F-box (SLF) proteins have been identified in Antirrhinum and several Prunus species. Although they appear to play an important role self-incompatible reaction, functional evidence is lacking. Here, we provide lines of directly implicating a AhSLF-S2 self-incompatibility Antirrhinum. First, nonallelic physical interaction between S-RNases was demonstrated by both coimmunoprecipitation yeast two-hybrid assays. Second, interacts with ASK1- CULLIN1-like...

In this paper we propose the graduated nonconvexity and concavity procedure (GNCCP) as a general optimization framework to approximately solve combinatorial problems defined on set of partial permutation matrices. GNCCP comprises two sub-procedures, which realizes convex relaxation concave relaxation. It is proved that exactly type convex-concave (CCRP), but with much simpler formulation without needing or in an explicit way. Actually, involves only gradient objective function therefore very...

High-precision manipulation is very important for a variety of tasks in manufacturing. In general, high-precision usually achieved by the guidance sensors; however, sensorless methods, some special cases, are more reliable and effective. There many works this aspect [1]-[3]. The concept "attractive region environment" (ARIE), which was proposed our previous [4]-[6], provides prospective approach low-precision systems to achieve manipulation. It has been used various industrial applications,...

Grasping and assembly are essential tasks in high-precision robotic manipulation for industrial manufacturing as well home service applications. Many efforts have been devoted to this area an attempt meet the increasing precision requirement of task. However, it remains a problematic objective fulfill high precision, reliability, speed, flexibility all at once during one To find answers above-mentioned problem, article tries categorize, review, compare recent works focusing on grasping...

In this article, an adaptive neural network control scheme is presented for uncertain wheeled mobile robot (WMR) with velocity constraints and nonholonomic constraints. practice, dynamic parameters of the system, which may change in some conditions, are hard to obtain precisely, WMR should be constrained safety. To deal uncertainty robot, networks used approximate unknown robotic dynamics, barrier Lyapunov function guarantee constraint on velocity. The tracking error closed-loop system...

Robust object detection methods in traffic surveillance scenarios often encounters challenges due to large-scale deformations and illumination variations outdoor scenes. To enhance the tolerance of such against these variations, we design a cross-scale illumination-invariant model (CSIM) based on You Only Look Once (YOLO) architecture. A main cause false tasks is inconsistency between various feature scales. address this issue, introduce an adaptive fusion ensure consistency constructed...

Spiking Neural Networks (SNNs) have attracted significant attention for their energy-efficient and brain-inspired event-driven properties. Recent advancements, notably Spiking-YOLO, enabled SNNs to undertake advanced object detection tasks. Nevertheless, these methods often suffer from increased latency diminished accuracy, rendering them less suitable latency-sensitive mobile platforms. Additionally, the conversion of artificial neural networks (ANNs) frequently compromises integrity ANNs'...

In this paper, a new concept called nonlinear measure is introduced to quantify stability of systems in the way similar matrix for linear systems. Based on concept, novel approach analysis neural networks developed. With approach, series sufficient conditions global and local exponential Hopfield type presented, which generalizes those existing results. By means measure, convergence rate stable equilibrium point estimated, and, stability, attraction region characterized. The developed can be...

In this paper, a novel methodology called reference model approach to stability analysis of neural networks is proposed. The core the new study network with other related models, so that different modeling approaches can be combinatively used and powerfully cross-fertilized. Focused on two representative (the neuron state local field approach), we establish rigorous theoretical basis feasibility efficiency approach. has been develop series new, generic theories for various models. These...

In this paper, we are concerned with the registration of two 3D data sets large-scale stretches and noises. First, by incorporating a scale factor into standard iterative closest point (ICP) algorithm, formulate constraint optimization problem over 7D nonlinear space. Then, apply singular value decomposition (SVD) approach to iteratively solving such problem. Finally, establish new ICP named Scale-ICP for isotropic stretches. order achieve global convergence proposed propose way select...

Manifold learning is a hot research topic in the held of computer science and has many applications real world. A main drawback manifold methods is, however, that there are no explicit mappings from input data to output embedding. This prohibits application practical problems such as classification target detection. Previously, order provide for methods, have been proposed get an approximate representation mapping with assumption exists linear projection between high-dimensional samples...

The support vector machine (SVM) method, as a promising classification technique, has been widely used in various fields due to its high efficiency. However, SVM cannot effectively solve online problems since, when new sample is misclassified, the classifier be retrained with all training samples plus sample, which time consuming. According geometric characteristics of SVM, this paper we propose an called VS-OSVM, based on convex hull vertices selection within each class. VS-OSVM algorithm...

In this paper, we present an overview of robotic peg-in-hole assembly and analyze two main strategies: contact model-based model-free strategies. More specifically, first introduce the model control approaches, including state recognition compliant steps. Additionally, focus on a comprehensive analysis whole system. Second, without process, decompose learning algorithms into subfields: from demonstrations environments (mainly based reinforcement learning). For each subfield, survey landmark...