This paper presents intelligent stereo matching algorithm (ISMA) to solve problems associated with matching stereo images. This algorithm adopts a two-dimensional Hopfield neural network (HNN) to match stereo pairs based on an energy function including three constraints referred to as uniqueness, similarity and compatibility. The similarity of a matched pair is obtained by identifying differenc...

In this paper, we aim to clarify the computational complexity of artificial neural networks. We investigate hysteresis networks (HNN) for solving constraint satisfaction problems. confirm that amount computation is proportional logarithm size problem.

Bài báo đề cập đến việc cải thiện độ chính xác của mô hình số cao (Digital Elevation Model - DEM). Mặc dù, các thuật toán tái chia mẫu song tuyến, bicubic, Kriging và tăng phân giải bằng mạng nơ ron Hopfield (HNN) cho phép nâng cao, đặc biệt là từ nguồn dữ liệu toàn cầu như SRTM, ASTER, v.v., sự tham gia bổ sung cũng có thể hơn nữa cao. này xuất một HNN với hàm hiệu chỉnh thay đổi điều kiện ràn...

9 The oligonucleotides coding for three epitopes (HA91–108, NP55–69, and NP 147–158) of influenza, virus stimulating B-cells, T-helper cells and cytotoxic T lymphocytes (CTLs), respectively, were previously employed for expressing each epitope in flagella that induced specific humoral and cellular immune responses. We have constructed new plasmids expressing all three epitopes as a single recom...

84 Abstract—In this paper, we analyze the convergence and stability properties of Hopfield Neural Networks (HNN). The global convergence and asymptotic stability of HNN have successful various applications in computing and optimization problems. After determining the mathematical model of the network, we do some analysis on the model. This analysis base on Lyapunov Stability Theorem. Firstly, w...

Conceptual cost estimates are important to project feasibility studies, even the final project success. The estimates provide significant information for project evaluations, engineering designs, cost budgeting and cost management. This study proposes an artificial intelligence approach, the evolutionary fuzzy hybrid neural network (EFHNN), to improve precision of conceptual cost estimates. The...

This paper developed an evolutionary fuzzy hybrid neural network (EFHNN) to enhance the effectiveness of assessing subcontractor performance in the construction industry. The developed EFHNN combines neural networks (NN) and high order neural networks (HONN) into a hybrid neural network (HNN), which acts as the major inference engine and operates with alternating linear and non-linear NN layer ...

Although the induction of fuzzy decision tree (FDT) has been a very popular learning methodology due to its advantage of comprehensibility, it is often criticized to result in poor learning accuracy. Thus, one fundamental problem is how to improve the learning accuracy while the comprehensibility is kept. This paper focuses on this problem and proposes using a hybrid neural network (HNN) to ref...

This paper proposes the optimization relaxation approach based on the analogue Hopfield Neural Network (HNN) for cluster refinement of pre-classified Polarimetric Synthetic Aperture Radar (PolSAR) image data. We consider the initial classification provided by the maximum-likelihood classifier based on the complex Wishart distribution, which is then supplied to the HNN optimization approach. The...

In this article, we continue our very recent work by extending it to the complex case. Having been inspired real Hopfield neural network (HNN) results, investigations here yield various novel some of which are as follows. First, “biased pseudo-cut” concept HNN (CHNN) case, introduce a “shadow-cut” that is defined sum intercluster phased edges. Second, while discrete-time strictly minimizes in e...