共查询到18条相似文献,搜索用时 203 毫秒
1.
2.
3.
一个改进的指数双向联想存储器及性能分析 总被引:1,自引:2,他引:1
通过分析Wang的修正指数双向联想存储器(MeBAM),本文提出了一个新的指数式双向联想存储器.该存储器不仅保持了MeBAM的优点,如放宽了Kosko对BAM的连续性假定的限制,排除了BAM的补码问题,同时还大大改善了现有BAM的存储性能和纠错能力.通过定义一个随状态变化而减少的能量函数严格证明了改进的eBAM(IeBAM)在同步与异步方式下的稳定,从而保证了所有要存的模式对成为其稳定点.此外,借助信噪比分析方法给出了IeBAM和MeBAM的信噪比估计.理论分析和计算机模拟结果证实了IeBAM的性能确实优于MeBAM和eBAM. 相似文献
4.
改进的指数双向联想记忆模型及性能估计 总被引:4,自引:1,他引:3
提出了一个新的改进型指数双向联想记忆模型(improved eBAM,简称IeBAM).通过定义有界且随状态改变而下降的能量函数,证明了IeBAM在状态的同、异步更新方式下的稳定性,一方面排除了Wang的修正指数BAM(modified eBAM,简称MeBAM)和Jeng的eBAM(exponential BAM)的稳定性证明中所作的不合理假设;另一方面,放宽了对BAM(bidirectional associative memory)的连续性假设的要求,并避免了补码问题.理论分析和计算机模拟结果表明, 相似文献
5.
多重加权多值指数双向联想记忆网络及其表决性能 总被引:2,自引:0,他引:2
Wang和陈等利用各自提出的二值指数双向联想记忆模型(eBAM)及其改进型eBAM(IeBAM),分别构造了由多个eBAM和IeBAM组成的多重eBAM(Multi-eBAM)和多重IeBAM(Multi-IeBAM)的信念组合模型,使之可模拟多个专家的表决。该文在此基础上,借助陈提出的多值eBAM(MVeBAM),提出了多重多值eBAM (Multi-MVeBAM),对Multi-eBAM和Multi-IeBAM进行了两方面的推广;一是将二值表示推广到多值表示,以此可以处理现实中的多值数据;二是将原有模型中具有同等权威度的各专家推广到各具不同的权威度的专家,以此模拟更实际的表决情形。文中借助能量函数证明了所提模型的渐近稳定性,以保证其实际可用。计算机模拟证实了模型的可行性。 相似文献
6.
提出了一个新的高阶双向联想记忆模型.它推广了由Tai及Jeng所提出的高阶双向联想记忆模型HOBAM(higher-order bidirectional associative memory)及修正的具有内连接的双向联想记忆模型MIBAM(modified intraconnected bidirectional associative memory),通过定义能量函数,证明了新模型在同步与异步更新方式下的稳定性,从而能够保证所有被训练模式对成为该模型的渐近稳定点.借助统计分析原理,估计了所提模型的存储容量.计算机模拟证实此模型不仅具有较高的存储容量,而且还具有较好的纠错能力. 相似文献
7.
推广了Wang的多值指数双向联想记忆(multi-valued exponential bi-directional associative memory,简称MV-eBAM)模型,使其成为所提出的推广的多值指数双向联想记忆 (extended MV-eBAM,简称EMV-eBAM) 模型的一个特例.EMV-eBAM具有比前者更高的存储容量和纠错性能,因此利用这种性能,设计了一种基于联想记忆的新型图像压缩算法.该算法在无噪声情况下具有与矢量量化(vector quantization,简称VQ)算法相近的性能,而在双重(信道和图像)噪声环境下则具有显著的抑制效果.对比实验结果显示,在添加5%椒盐噪声下,该算法几乎能完全排除噪声干扰,而VQ则反而放大了噪声.该算法的另一个优点是,当在差错信道中传送时,可以获得比采用循环纠错码更强的纠错性能.因而,该算法具有较强的鲁棒性. 相似文献
8.
为解决实时数据库数据量大导致存储困难等问题,提出一种分类的数据压缩算法,实现对实时数据库数据的无损和高效压缩。首先将实时数据库的数据分为数值、时间戳和质量码3部分,然后根据每种数据的特征形态,将LZ78和LZW数据压缩算法融合,分别设计对应的数据压缩算法。实验结果表明,该算法在提高数据库的实际存储容量的同时也提高了实时数据库的实时性。
相似文献
9.
传感器网络中一种存储有效的小波渐进数据压缩算法 总被引:2,自引:0,他引:2
现有的数据压缩算法大多以节能为设计目标,很少顾及到节点有限的存储容量.设计适合传感器网络小波变换的环模型和基于覆盖重叠的分簇模型,消除边界效应.基于此两种网络模型,分别提出存储有效的二维和三维渐进小波数据压缩算法,该算法依据小波函数的支撑长度和簇头的可用存储容量来确定渐进传送的数据单元,具有存储有效性;依据空间相关性来选择渐进传送数据的传感器节点,从而在存储有效的同时又节省网络传输耗能.从存储开销、能量消耗和网络延时等3个方面分析了算法的性能.理论分析和实验结果表明,和一般的数据压缩算法相比,小波渐进压缩算法在耗能相当的情况下,节省了节点的存储容量. 相似文献
10.
11.
Data compression by the recursive algorithm of exponentialbidirectional associative memory 总被引:1,自引:0,他引:1
Chua-Chin Wang Chang-Rong Tsai 《IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics》1998,28(2):125-134
A novel data compression algorithm utilizing the histogram and the high-capacity exponential bidirectional associative memory (eBAM) is presented. Since eBAM has been proved to possess high capacity and fault tolerance, it is suitable to be utilized in the data compression using the table-lookup scheme. The histogram approach is employed to extract the feature vectors in the given data. The result of the simulation of the proposed algorithm turns out to be better than the traditional methods. 相似文献
12.
提出了新的二进制(位级)无损图像压缩方法——将错误纠正BCH码引入到图像压缩算法中;将图像的二进制分为大小为7的码字,这些块进入到BCH解码器,消除了校验位后,使得原来的块的大小减少到4位。实验结果表明,此压缩算法是有效的,并给出了一个很好的压缩比,而且不丢失数据。BCH码的使用在提高压缩比方面比单纯霍夫曼压缩的结果要好。 相似文献
13.
Chua-Chin Wang Chenn-Jung Huang Shiou-Ming Hwang 《IEEE transactions on systems, man, and cybernetics. Part A, Systems and humans : a publication of the IEEE Systems, Man, and Cybernetics Society》2000,30(6):817-819
The multi-valued exponential bidirectional associative memory (MV-eBAM) has been proposed and proved to be asymptotically stable under certain constraints. Although multi-valued eBAM has been verified to possess high capacity by thorough simulations, the capacity is still unable to be solved analytically. In the paper, an algorithm is proposed to derive the capacity. Some important characteristics, including the absolute lower bound of the radix, and the approximate capacity are also discussed. The result shows that the multi-valued eBAM indeed possesses high capacity 相似文献
14.
Capacity analysis of the asymptotically stable multi-valuedexponential bidirectional associative memory 总被引:1,自引:0,他引:1
Chua-Chin Wang Shiou-Ming Hwang Jyh-Ping Lee 《IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics》1996,26(5):733-743
The exponential bidirectional associative memory (eBAM) has been proposed and proved to be a stable and high capacity associative neural network. However, the intrinsic structure and the evolution functions of this network restrict the representation of patterns to be either bipolar or binary vectors. We consider the promising development of multi-valued systems and then design a multi-valued discrete eBAM (MV-eBAM). The multi-valued eBAM has been proved to be asymptotically stable under certain constraints. Although MV-eBAM is also verified to possess high capacity by thorough simulations, there are important characteristics to be explored, including the absolute lower bound of the radix, and the approximate capacity. In order to estimate the capacity of the MV-eBAM, a modified evolution equation is also proposed. Hence, an analytic solution is derived. Besides, a radix searching algorithm is presented such that the absolute lower bound of the radix for this MV-eBAM can be found. 相似文献
15.
16.
17.
An analysis of high-capacity discrete exponential BAM 总被引:4,自引:0,他引:4
Chua-Chin Wang Hon-Son Don 《Neural Networks, IEEE Transactions on》1995,6(2):492-496
An exponential bidirectional associative memory (eBAM) using an exponential encoding scheme is discussed. It has a higher capacity for pattern pair storage than conventional BAMs. A new energy function is defined. The associative memory takes advantage of the exponential nonlinearity in the evolution equations such that the signal-to-noise ratio (SNR) is significantly increased. The energy of the eBAM decreases as the recall process proceeds, ensuring the stability of the system. The increase of SNR consequently enhances the capacity of the BAM. The capacity of the exponential BAM is estimated. 相似文献