Current-feedback magnetic multivibrators are widely used as power sources for electronic equipment, because they are highly efficient and reliable. However, these circuits have no ability to protect themselves from ov...
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Current-feedback magnetic multivibrators are widely used as power sources for electronic equipment, because they are highly efficient and reliable. However, these circuits have no ability to protect themselves from overloading, and the oscillation frequency changes according to the load current. In this paper, we propose a new current-feedback multivibrator with overload protection and frequency compensation. In addition, the condition for cessation of oscillation and that for fixed frequency of oscillation are derived by analysis. These conditions can be determined independently of each other.
This paper is concerned with an application of a digital adaptive control system to a servo mechanism. Mechanical systems in general include nonlinearities and additional uncertainties and which result from inertia an...
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This paper is concerned with an application of a digital adaptive control system to a servo mechanism. Mechanical systems in general include nonlinearities and additional uncertainties and which result from inertia and friction. So it is difficult to ensure robust performance and high accuracy for motion control. The digital adaptive control system presented here is considered to overcome the above stated problem. Experimental results from a feed drive system demonstrate the effectiveness of the proposed control scheme.
In transport layer protocols over ATM networks, a packet is discarded when one or more cells are lost in that packet, and the destination node then requires its source to retransmit the corrupted packet. Therefore, on...
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In transport layer protocols over ATM networks, a packet is discarded when one or more cells are lost in that packet, and the destination node then requires its source to retransmit the corrupted packet. Therefore, once one of cells constituting a packet is lost, its subsequent cells of the corrupted packet waste network resources. In this paper, we propose the throughput analysis in transport layer with selective cell discard schemes and selective repeat ARQ. In the analysis, we suppose that sources steadily generate cells due to the packet retransmission; the resulting state will be referred to as source saturation, which makes the analysis very tractable from a computational point of view. Through some numerical results, we can clarify the impacts of the average number of packet length, the buffer size and the number of sources on the throughput performance of selective cell discard schemes.
A practical structural representation of a segmented image is presented. The practicalness is defined according to whether or not: the representation can be directly generated from its corresponding segmented image. T...
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A practical structural representation of a segmented image is presented. The practicalness is defined according to whether or not: the representation can be directly generated from its corresponding segmented image. Two structural representations have been proposed in the literature. They are hierarchical structure and relational graph. Because they are defined totally on the basis of human perception, neither of the representations can be directly generated from the corresponding segmented image. The structural representation described in this paper, however, is based on the relations among pattern primitives and generated by applying some human-oriented constraints.
From a GF(q) sequence {a(i)}(i greater than or equal to 0) with period q(n)-1 we can obtain new periodic sequences {(a) over cap(i)$}(i greater than or equal to 0) with period q(n) by inserting one symbol b is an elem...
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From a GF(q) sequence {a(i)}(i greater than or equal to 0) with period q(n)-1 we can obtain new periodic sequences {(a) over cap(i)$}(i greater than or equal to 0) with period q(n) by inserting one symbol b is an element of GF(q) al the end of each period. Let b(0) = Sigma(i=0)(qn-2) a(i). It is first shown that the linear complexity of {<(a)over cap(i)>}(i greater than or equal to 0), denoted as LC({(a) over cap(i)$}), satisfies LC({(a) over cap(i)$}) = q(n) if b not equal -b(0) and LC({(a) over cap(i)$}) less than or equal to q(n)-1 if b = -b(0). Most of known sequences are shown to satisfy the zero sum property i.e., b(0) = 0. For such sequences satisfying b(0) = 0 it is shown that q(n)-LC({a(i)}) less than or equal to LC({(a) over cap(i)$}) less than or equal to q(n)-1 if b = 0.
There have been numerous methods for learning and predicting time series ranging from the traditional time-series analyses to recent approaches using neural networks. A central issue common to all of them is the deter...
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There have been numerous methods for learning and predicting time series ranging from the traditional time-series analyses to recent approaches using neural networks. A central issue common to all of them is the determination of model structure. Both mean prediction error and An Information Criterion (AIC) are useful in model selection;the model with the smallest mean prediction error or AIC is selected from among a set of models as the best one. In this way they give a solution to the problem of model selection. Due to huge search space, however, the mean prediction error or AIC alone is not powerful enough to find the best model structure from among all the candidates. In the present paper the authors propose to use both a structural learning with forgetting and the mean prediction error or AIC to find a model with better generalization ability. Jordan networks and buffer networks, popular in the modeling of time series, are examined in this paper. The structural learning with forgetting and backpropagation (BP) learning are applied to compare the learning and prediction performance of these two types of models. Simulation results demonstrate that the structural learning with forgetting has better generalization ability than BP learning both in Jordan networks and buffer networks.
The Saccharomyces cerevisiae ire15 mutant has a defect in the expression of the INO1 gene, showing an inositol auxotrophic phenotype. The growth defect of this mutant is suppressed by human cDNAs such as for the TGF-b...
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The Saccharomyces cerevisiae ire15 mutant has a defect in the expression of the INO1 gene, showing an inositol auxotrophic phenotype. The growth defect of this mutant is suppressed by human cDNAs such as for the TGF-beta receptor-encoding gene (TGFR) [Nikawa, Gene 149 (1994) 367-372]. Here, we isolated a new human cDNA, HCP1, which suppresses the ire15 mutation by genetic complementation. Sequencing analysis revealed that HCP1 encodes 360 amino acid residues (40515 Da). The product of HCP1 is highly conserved among species and the yeast homolog was also found to suppress the ire15 mutation. Northern blot analysis revealed that multicopies of the yeast and human HCP1, as well as TGFR, resulted in an increase in the INO1 mRNA level in the yeast mutant. These results clearly indicate that the products of human and yeast HCP1 are structural and functional homologs, and are involved in expression of genes such as of INO1.
This paper describes a fuzzy neuron chip which is the modification of an ordinary neuron model by fuzzy logic, The algebraic product of scalar input and connective weights in synapse is replaced with a fuzzy inner pro...
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This paper describes a fuzzy neuron chip which is the modification of an ordinary neuron model by fuzzy logic, The algebraic product of scalar input and connective weights in synapse is replaced with a fuzzy inner product. An excitatory connection is represented by a MIN (minimum) operation and an inhibitory connection by fuzzy logic complement followed by a MIN operation;While an ordinary neuron model is established only by leaning, the fuzzy neuron is designable and optimized by learning, The fuzzy neuron is implemented in silicon wafer by a standard BICMOS process. The chip is applied to a handwritten character recognition system and it exhibits very high-speed recognition (less than 500 ns).
This paper compares the performance of an indoor cellular system in terms of capacity and channel assignment delay for different Dynamic Channel Assignment (DCA) and Fixed Channel Assignment (FCA) schemes. We refer to...
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This paper compares the performance of an indoor cellular system in terms of capacity and channel assignment delay for different Dynamic Channel Assignment (DCA) and Fixed Channel Assignment (FCA) schemes. We refer to specific group of DCAs, namely Channel Segregation and Reuse Partitioning (RP). Our main concern is to show that these DCA schemes offer better performance than FCA. Since the structure and floor layout of a building will have a major influence on the propagation and hence on the cell shape, a path loss simulator is developed for predicting the path loss which is used in evolving base station layouts. computer simulation, based on Monte Carlo method, is carried out using the path loss values and the base station layouts. The results indicate that increased traffic capacity can be achieved with ail DCAs in comparison with FCA. The highest capacity and a shorter channel assignment delay are delivered by Self-Organized Reuse Partitioning DCA scheme.
This work reconstructs 3D graphics model of an object from an image sequence taken during the object rotation. Shading and its motion information are used in estimating shapes of smooth surfaces between fixed edges fr...
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