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Following the computation of the factors [L] and [U] it is a simple matter to obtain the column matrix (x) as follows. The first step (forward substitution) is to compute a column matrix (z) = [U](x) by solving the linear system [L](z) = (b). The second step (backward substitution) involves the computation of (x) from [U](x) = (z). We shall not go into the details of the decomposition process here. The interested reader can find them in almost any book on numerical methods. The entire method can be programmed in only a few lines of computer code (see, e.g., Press et al., 1992). The LU decomposition method is particularly useful for solving linear systems of the form [^4][X] = [B], where [X] and [B] are rectangular (i.e., with more than one column).

Figure 10.9 Control variables in the torque speed characteristics of the induction generator: a stator voltage; b rotor voltage; c stator rotor voltage phase shift; d rotor resistance; e rotor reactance; f stator voltage; g number of stator poles.

This time we re going to integrate the XML toolset into the Web layer. The Apache FOP tool is commonly used in J2EE applications to present data in .pdf format, so that s the example we ll tackle. We ll build a servlet that takes in the FO document as a parameter and transforms that XML document into a .pdf file. Our servlet code is actually quite simple. All the heavy lifting is done for us by the Apache FOP library. In order to test this, you ll need to have Tomcat running. If you haven t set this up already, please refer to 5. Here s the source code for SimpleFopServlet.java:

system has = 0 The following diversity gain (dB) at the 90% signal reliability level has been found empirically for the various combining techniques [13, p 48]: MRC 714e 059 e 011 EGC (12-36) Gain (dB) = 898 + 1522e 02 e 004 087 016 571e e SEC MRC always produces a positive diversity gain Selecting the larger signal has less bene t than MRC, and the EGC system can actually give a negative diversity gain under unfavorable situations If the signal drops in one channel, adding two signals reduces overall performance because in essence the high signal level channel is reduced by 3 dB by the power divider Adaptive arrays (smart antennas) improve the system by directing a main beam at a particular user while producing nulls in directions of interfering signals.

There were 40 people at the meeting, although half of them were in the hallway on cell phones, responding to the latest crises. Esther tapped the microphone and asked everyone to take their seats while Frank worked with the Professor s laptop and the overhead display. Font problems. A few more attendees came into the room, pausing at the table for bottles of water before taking their seats near the rear. Even when there are empty seats in the front row, students avoid sitting too close to the speaker out of fear, reinforced by too many years in classrooms, that they will be called on for the answer to an unanswerable question.

These signals could be from nearby cells using the same frequencies Adaptive receiving arrays enable closer frequency reuse between cells and increases system capacity while improving quality of transmission We either adaptively control element excitation at RF or detect and combine them at IF The weak link in the cellular telephone system is the transmission from the mobile to the base station, and the base station contains the array used to separate signals, so we concentrate on the receiving path The array either uses the least mean squares (LMS) algorithm or an eigendecomposition technique to set the element weights LMS requires a known reference signal on which the system minimizes the errors This system adjusts the weights to maximize the S/N ratio.

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The known signal can be a portion of the coded waveform transmitted by the mobile unit, which increases overhead and reduces transmit rate slightly when each unit sends a unique reference signal The LMS algorithm can adjust weights to optimize the constant amplitude of receive signal, since a phased modulated wave (PSK, QPSK) has constant amplitude Systems that optimize on a known reference signal include recursive least squares and Wiener lter methods Eigen-decomposition techniques operate without a known reference signal A crosscorrelation matrix is formed from the input signals by considering their locations using the terms of Eq (12-29) A cross-correlation matrix is the product of the pairs of these terms using the complex conjugate of one factor By solving the eigenvalue problem, the algorithm detects directions of incoming signals and the beamforming is based on the angular information of these beams Two commonly used algorithms are MUSIC and ESPRIT.