The detection probability computation of single stuck-at-faults in general combinational circuits

The detection probability problem of single faults at specified signal lines of a general combinational circuit C merits special interest. In this paper, a method is developed for such a purpose. The method has a computational complexity of O(2^N), with N being the number of the non-fanout primary inputs plus the specified signal lines at the highest level of C. The applicability of the simple chain rule in the probability domain, whenever possible, is shown to reduce the computational time complexity. Moreover, all signal lines and gates within any subcircuit C_i of C with redundant output lines are shown to be redundant as well, excluding those subcircuits C_js of C_i having fanout stems as output lines, provided that such stems do not converge in C_i     

Output process from a continuous token ring local area network

A token-ring local area network (LAN) with an infinite number of nodes uniformly distributed around the ring is considered. A token that circulates around the ring at a constant speed stops to serve fixed length packets that are generated by the nodes. It is assumed that the cumulative arrival process of packets constitutes a two-dimensional Poisson process. Given a fixed point on the ring, called the origin, the first-order statistics of the interarrival times of packets at the origin are obtained in the form of their Laplace-Stieltjes transform     

A novel design of a combinational network to facilitate fault detection

This letter describes a novel design of a combinational network to facilitate the single stuck-at fault detection problem. The design makes use of EXCLUSIVE-OR modules as control elements and the observability has been increased by providing an additional observable output which is the output of an additional AND gate in the network. Such a design of a combinational network with n primary input variables will require only (n + 1) predefined test input patterns belonging to the set T = {11...11,011...11,101 ...11, ........., 11 ... 110} for the detection of stuck-at single s-a-0 and s-a-1 fault on a line of the network. As a result, the extremely difficult task of test generation can be easily dispensed with.     

Novel probability neural network

This paper presents a novel probability neural network (PNN) that can classify the data for both continuous and categorical input data types. A mixture model of continuous and categorical variables is proposed to construct a probability density function (PDF) that is the key part for the PNN. The proposed PNN has two advantages compared to conventional algorithms such as the multilayer perceptron (MLP) neural network. One is that the PNN can produce better results compared to the MLP neural network when the input data set includes both continuous and categorical data types, even using the normalised input variables. Normally, the normalised input variables generate a better result than the non-normalised input variables for the MLP neural network. The second advantage is that the PNN does not need the cross-validation data set and does not produce over-training like the MLP neural network. These advantages have been proven in our experimental study. The proposed PNN can also be used to perform unsupervised cluster analysis. The superiority of the PNN, compared to the MLP neural network, Radical Basis Function (RBF) neural network, C4.5 and Random Forest decisions trees, are demonstrated by applying them to two real-life data sets, the Heart Disease and Trauma data sets, which include both continuous and categorical variables.     

DECISION OF OPTIMAL HOPFIELD NEURAL NETWORK MODEL OF COMBINATIONAL CIRCUITS

By use of Hopfield model and basis solution of homogeneous linear equations which are established in accordance with consistent state, a practical decision method for the existence of optimal Hopfield model of combinational circuits is provided. Finally, an example is given.     

NS网络仿真技术及其结果输出和分析

为了在仿真环境下对网络协议进行性能评价，必须对仿真结果进行有效的分析和处理。介绍了NS网络仿真器的两层体系结构，描述了跟NS相关的几个常用工具，然后以实例说明了如何根据自己的需要在仿真脚本中对数据进行处理，只输出感兴趣的结果。     

Extension of Boolean differentiation to define a test for a specific logic fault in a combinational logic network

The letter demonstrates an extension of Boolean difference to obtain a test for a specific fault. The extension is compared with Roth's D calculus, and it is shown that the two concepts are complementary. A procedure for determining the total fault-detection capability of each test is indicated.     

A neural network algorithm for testing stuck-open faults in CMOS combinational circuits

In this article, an automatic test pattern generation technique using neural network models for stuck-open faults in CMOS combinational circuits is presented. For a gate level fault model of stuck-open faults in CMOS circuits, SR(slow-rise) and SF(slow-fall) gate transition faults we develop a neural network representation. A neural network computation technique for generating robust test patterns for stuck-open faults is given. The main result is extending previous efforts in stuck-at test pattern generation to stuck-open test pattern generation using neural network models. A second result is an extension of the technique to robust test pattern generation.     

Exact symbol error probability of a Cooperative network in a Rayleigh-fading environment

In a distributed spatial diversity wireless system, not all antennas are located at one station as in classical transmit diversity systems, but are dispersed at different, possibly mobile, stations in the network. Transmit diversity is created when the selected stations assist a sender by relaying its information signal to the destination. In this letter, we present an exact average symbol error rate analysis for the distributed spatial diversity wireless system with K amplifying relays in a Rayleigh-fading environment. The average symbol error rate formula allows us to clearly illustrate the advantage that the distributed diversity system has in overcoming the severe penalty in signal-to-noise ratio caused by Rayleigh fading. Using simple bounds on the probability of error, we show that the cooperative network presented in this letter achieves full diversity order.     

Calculating the outage probability in a CDMA network with spatialPoisson traffic

In this paper, we provide a spatial Poisson point pattern model of traffic in a code division multiple access (CDMA) wireless network. We show how the theory of Poisson processes can be applied to provide statistical information about interference levels in the network. In particular, we calculate approximations and a bound on the outage probability at a designated cell site in the network, utilizing high-order cumulants, which have very simple analytical forms and can easily be computed once the mean measure of the spatial Poisson point pattern is known. We consider a Poisson-Gaussian approximation and an Edgeworth approximation in which the Gaussian distribution is twisted to satisfy the required cumulants, and we provide a Chernoff bound on performance that also utilizes the cumulant information. We show that the theory can be applied to nonstationary, time nonhomogeneous systems. We provide a particular example of a M/M/∞, spatial queueing model of a CDMA wireless network     

FIRE: a fault-independent combinational redundancy identificationalgorithm

FIRE is a novel Fault-Independent algorithm for combinational REdundancy identification. The algorithm is based on a simple concept that a fault which requires a conflict as a necessary condition for its detection is undetectable and hence redundant. FIRE does not use the backtracking-based exhaustive search performed by fault-oriented automatic test generation algorithms, and identifies redundant faults without any search. Our results on benchmark and real circuits indicate that we find a large number of redundancies (about 80% of the combinational redundancies in benchmark circuits), much faster than a test-generation-based approach for redundancy identification. However, FIRE is not guaranteed to identify all redundancies in a circuit     

Evaluation of probability mass function of flow in a communication network considering a multistate model of network links

This paper presents two efficient algorithms for exact evaluation of probability mass function (pmf) from source node to sink node of a large communication network considering a multistate capacity model of links, using composite path and composite cut methods. The capacities of various states of each link of the network are assumed to be mutually exclusive. From the pmf the performance index is obtained without difficulty. The applicability of the proposed algorithms has been tested for various networks (two-state and multistate). However, the latter method (composite cut) is found to be more efficient. An interesting finding is that when a three-state model is replaced by an analogous two-state model, system reliability is underestimated. Thus, if a system is to be represented by a multistate model, one should not use a simplified two-state model for mathematical convenience alone.     

An analytical model on network blocking probability

We present a new analytical model on the blocking probability of the three-stage Clos (1953) network. Due to the effect of approximations, a common problem with previously proposed analytical models is that they may not be very accurate in some cases. In particular, the blocking probability in these models contradicts the well-known deterministic nonblocking condition for the Clos network. The most notable feature of the newly proposed model is that it can more accurately describe the blocking behavior of the network and is consistent with the deterministic nonblocking condition     

A partitioning technique for reducing the computational complexity of probabilistic fault detection in general combinational circuits

This paper examines the impacts of different types of circuit partitioning on reducing the computational complexity for computing the fault detection probability, which usually grows exponentially with the number of input lines in the given circuit. Partitioning a large combinational circuit into arbitrary subcircuits does not, in general, reduce the computational time complexity of the fault detection probability. In fact, partitioning a given circuit into general subcircuits is expected to increase the time complexity by the amount of time spent in the partition process itself. Nevertheless, it will be shown that decomposing a general combinational circuit into its modules (supergates) such that these modules constitute the basic elements of a tree circuit (network) considerably reduces the computational complexity of the fault detection probability problem. Toward this goal, two algorithms are developed. The first partitions a given circuit into maximal supergates whenever this is possible. Its computational complexity depends linearly on the number of edges (or lines) and nodes (or gates) of the circuit. The second computes the exact detection probabilities of single faults in the tree network and its computational complexity grows exponentially with the largest number of input lines in any of the network maximal supergates rather than the total number of inputs. The case of multi-output circuits is also discussed.     

An efficient tag-based routing algorithm for the backward network of a bidirectional general shuffle-exchange network

This letter considers the problem of designing efficient routing algorithms for the backward network of a bidirectional general shuffle-exchange network (BNBGSEN for short); switch elements in the network are of size k/spl times/k. It has been shown in (Z. Chen, et al., 2003) that the algorithm in (K. Padmanabham, 1991) can be used to obtain (as many as k) backward control tags for a source j to get to a destination i in a BNBGSEN. In this letter, we show that a BNBGSEN has a wonderful property: for each destination i, there are two backward control tags associated with it such that every source j can get to i by using one of the two tags. We use this property to derive an efficient tag-based routing algorithm.     

Topological and sensitivity formulas for a general nonreciprocal 2-port network

Topological formulas, which involve a minimum of algebraic redundancy, are given for ? directed-tree Y products and sensitivities for a general nonreciprocal 2-port network.     

Fault detection in combinational circuits using a compressed fault table

A method is developed for obtaining a highly compressed fault table for two-level combinational circuits. A set of operations is defined through which the minimal test set for detecting stuck-at faults is obtained from the compressed fault table. The method is equally suitable for sum of products form or product of sums form realization of logic functions and generates the test set directly from the algebraic expression of the logic function.     

Carrier sensing range analysis in a general IEEE 802.11 network with physical‐layer network coding

In this paper, we investigate the carrier sensing range (CSR) of a general 802.11 network with physical‐layer network coding (PNC). We aim to derive a sufficient CSR that can prevent the hidden‐node collisions in a general 802.11 PNC network. The analysis includes two steps. First, we analyze the six link‐to‐link interference cases in an 802.11 PNC network to show that the mutual interference will be most severe when each node in the network initiates a two‐hop end node link. Second, we consider the worst interference case that all concurrently transmitting links in the network are two‐hop end node links and placed in the densest manner and develop a closed‐form expression of a sufficient CSR that prevents the hidden‐node collisions in a PNC network. From the analysis results, we find that to prevent the hidden‐node collisions, the CSR in PNC network should be bigger than the one in traditional non‐network‐coding network. Furthermore, we carry out extensive simulations to find out the throughput gain of PNC scheme in a general wireless network when considering the impact of CSR. Simulation results show that compared with the non‐network‐coding scheme, PNC scheme has throughput gain when a large proportion (i.e., 90%) of links in the network are two‐hop links and the link density has little effect on the throughput gain of PNC scheme. Copyright © 2014 John Wiley & Sons, Ltd.     

A general approach to network analyzer calibration

A general-purpose algorithm, the TCX algorithm, for network analyzer and test fixture calibration is presented. The algorithm can handle most of the existing calibration methods, including symmetrical test fixtures. Any combination of one-port or two-port standards can be used. There is a possibility of partial self-calibration, if one of the standards is a two-port network or a through connection. The algorithm is applied to get simple equations covering the TSD, LDX (LRL), LAX, and LMX methods (X being an unknown one-port or symmetrical two-port network). A transmission path is allowed between the ports of standard X. In the TSD method, the delay line can be replaced with an attenuation network or with a matched load; also, the through line can have an unknown delay line and attenuation. A method of root choice for LRL and similar methods in conjunction with test fixtures is described. The method of least-squares-fit can be applied, when redundant data are available. It gives an essential improvement of accuracy in the simulation of a symmetrical test fixture