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The successful demonstrations of synchronization and data transmission in experiments have proved that these schemes are robust to some degree, but there is much still to be done in terms of evaluating the robustness and practical trade-offs with the security based on parameter sensitivity. A system based on the use of synchronization for replication will necessarily have some allowance for parameter mismatches. The smaller this allowance, the greater the security can be if the parameters are used as secret keys. On the other hand, the sensitivity of the lasers to changes in parameter may cause difficulties for stable operation. In this section we consider the issue of parameter mismatches with respect to chaos synchronization. But first we make a comment on the issue of security. Another aspect to the security of messages hidden in chaotic waveforms is the difficulty of separating the message from the chaotic carrier by analyzing recorded waveforms. It has been demonstrated that systems with low-dimensional chaos are not secure for data transmissions, in the sense that a low dimensional attractor is easily reconstructed from time series data, and system parameters are easily estimated from this attractor [44, 45]. Decoding without knowing key parameters becomes more difficult with the increase of the dimension of the chaotic dynamics [46]. The system of a semiconductor laser with optical feedback, as described by the theoretical model, is embedded in an infinite dimensional system due to the delay. However, the actual dimension of the dynamics is typically much lower, being restricted by the intrinsic response times in the laser. Quantitative analysis of the dimension of the synchronized chaos and the degree of security remains an important challenge for future study. Here we limit our discussion to the issue of the matching of the receiver laser for message recovery by synchronization.

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In general, the xed nodes with the strongest received signal powers are selected to provide the TOA estimates and their position coordinates are employed for the mobile tag position estimation There are many position estimation techniques using radio signals Signal strength, angle of arrival, TOA measurements, time of ight/round trip time, and TDOA can all be exploited for position estimation The most straightforward way to estimate position is to directly solve a set of simultaneous equations [4] based on the TOA/TDOA measurements Exact solutions can be obtained for 2-D location with two xed nodes using two TOA measurements (with known transmit time) or with three xed nodes using three TDOA measurements For a 3-D location, four xed nodes are needed to obtain exact solutions using TDOA measurements.

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For an over-determined system (with redundant xed nodes), several different approaches have been proposed such as spherical interpolation [5 8], the twostage maximum likelihood method [9], and the linear-correction least square approach [10] Also several iterative approaches have been investigated for position estimation Taylor series expansion can be used to iteratively produce a linear least-square solution [11, 12] However, to maintain good convergence, the Taylor series method may require a close estimate of the actual location as a starting point which may be dif cult to obtain in some practical applications A different iterative method for location comes from nonlinear optimization theory The gradient-based algorithms may be employed for position estimation [13, 14] One is the quasi-Newton algorithm [15], which has been used in the UWB precision assets location system [16] The other is the Gauss Newton type Levenberg Marquardt method [17].

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When you have implemented your Enterprise bean classes, and created the associated remote and home interfaces for each class, you must still write your client code Simple client applications resemble clients for RMI systems They start with a standard sequence of code used to establish contact with the server (in the case of a servlet client, this would best be done in the servlet s init method) Where an RMI client will typically be trying to create a proxy for some object identified in the rmiregistry, an EJB client will be trying to get a proxy for a Home object in the EJB container If the connection attempt is successful, the client will then use this initial Home proxy object to submit a create or find request for the actual session or entity bean with which it wishes to work.

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