### Table 2: Results for on-line checking

1998

"... In PAGE 6: ... For each set of faults we have applied 1000 pseudorandom inputs. The experimental results are represented in Table2 . The values for 1 and 2 in percent are given in column 2 and 3 respectively.... ..."

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### Table 7. Results for on-line framework tracking an applied goal.

"... In PAGE 94: ...2. Table7 shows the performance of our on-line adaptation framework, together with the onLineAdaptationTr and onLineAdaptationPower functions, for various goals applied to several DSP benchmarks. The starting schedule that is refined is found, as with the other experiments in this section, by using the standard critical path scheduling algorithm.... In PAGE 95: ...053), (T, 215), (P, 0.050), (T, 210), P} In Table7 , the column titled Goal represents the goal that is applied to the application. Also, for a non-negative integer , column denotes the value of a metric of the best schedule found by the on-line adaptation framework, after schedules have been assessed by executing them for some time.... In PAGE 95: ... Also, for a non-negative integer , column denotes the value of a metric of the best schedule found by the on-line adaptation framework, after schedules have been assessed by executing them for some time. For the same exper- iments, which are reported in Table7 , Table 8 shows the times at which different constraints associated with the applied goals, are satisfied. For a given goal that is applied on an application, for non-negative integers and , denotes the number of schedules that have been executed in order to assess them before the th con- straint in the applied goal is satisfied.... ..."

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### Table 8. Results for on-line framework tracking an applied goal.

"... In PAGE 95: ... Also, for a non-negative integer , column denotes the value of a metric of the best schedule found by the on-line adaptation framework, after schedules have been assessed by executing them for some time. For the same exper- iments, which are reported in Table 7, Table8 shows the times at which different constraints associated with the applied goals, are satisfied. For a given goal that is applied on an application, for non-negative integers and , denotes the number of schedules that have been executed in order to assess them before the th con- straint in the applied goal is satisfied.... ..."

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### Table 4: On-line classi cation performance

"... In PAGE 12: .... For all the cases we set = 0:5 and = 0:05 with one-pass learning. When on-line learning is applied, the ESOM is rst evolved with the training data and then with the test data. The on-line classi cation performance of ESOM network is given in Table4 , with an overall error rate of 3.4% tested with the two data sets.... ..."

### Table 3 Stages of the on-line personal ad

"... In PAGE 5: ... However, several modifications to the initial classification were required. The stages observed in this study are provided in Table3 . The discussion follows.... In PAGE 5: ...Table 3 Stages of the on-line personal ad The classification of generic stages provided in Table3 is different from the one proposed by Vlckova (1996) (see section 3.2.... In PAGE 5: ...e. the use of second person subject personal pronouns) has been labeled Reader-Orientation, and as seen in Table3 , may occur as a sub-stage in a variety of stages. This persuasive character of on-line personal ads, however, is not only realized through the Opening and Closing stages, or through Reader-Orientation.... ..."

### Table 1. Comparison to Gaussian RBF with on-line learning.

"... In PAGE 4: ... The selective forgetting algorithm was applied to compute the second layer weights. Table1 summarises the one step ahead prediction results. It can be seen that the proposed neuro-fuzzy learning algorithm has a similar performance to the RBF with 20 hidden units.... ..."

### Table 1: Signal objects de ned in SignalProcessing`Support`. For the syntax of CPulse, Dirichlet, FIR, IIR, LineImpulse and Pulse, consult the on-line documentation (e.g., ?CPulse).

"... In PAGE 5: ... We now examine them in more detail. Table1 lists the twelve new functions. There are discrete and continuous versions of the impulse (Impulse and Delta), step (Step and CStep), and pulse functions (Pulse and CPulse).... In PAGE 8: ... (However, certain obvious simpli cations are carried out: for example, InvZ[z,n][Z[n,z][f]] reduces to f.) Similarly, the functions of in Table1 are not reduced to Mathematica built-in objects until they appear as arguments to TheFunction. One may wish to reduce them, for example, in order to use Mathematica apos;s built-in plotting routines to plot them.... In PAGE 8: ... One may wish to reduce them, for example, in order to use Mathematica apos;s built-in plotting routines to plot them. Naturally, some functions in Table1 , like Delta and Unit, cannot be expressed in terms of Mathematica built-in objects, so TheFunction leaves them alone. Other Features Another facility provided by SignalProcessing`Support` is the plotting of signals and transforms.... In PAGE 18: ... Transforms of exponentials in the time domain are inverse-transformed by the exponential property rule, not by table lookup. Some strategies for inverting z-transforms ( Table1 0) are similar to those applied in taking forward z-transforms, but some new ones are also needed. Two such strategies are partial fractions and power series expansion.... In PAGE 19: ... complex cepstrum: Z?1flog X(z)g ! ? 1 nZ?1 ( z X(z) d dz X(z)) *9. apply the inverse z-transform to the rst N terms of a series expansion about z = 0 Table1 0: Strategies for inverse z-transforms. An asterisk means that once the rule is applied to an expression, it will no longer be applied to any part of that expression.... In PAGE 33: ...designing/analyzing 1-D analog lters DTFT discrete Fourier analysis EducationalTool interactive version of a conference paper describ- ing educational impact of Mathematica LaPlaceTest testing procedure for Laplace transforms PiecewiseConvolution tutorial on discrete/continuous convolution README brief introduction SignalProcessingExamples interactive version of paper in the The Mathemat- ica Journal SignalProcessingIntroduction introduction to Mathematica, signal processing, and the signal processing packages SignalProcessingUsage usage information about every new object de ned by the signal processing packages zTransformI z-transform tutorial, part I zTransformII z-transform tutorial, part II zTransformIII z-transform tutorial, part III Table1 1: List of the signal processing Notebooks transforms as long as the options are set properly. The default options are biased toward DTFT apos;s: Domain - gt; Continuous, DomainScale - gt; Linear, MagRangeScale - gt; Linear, PhaseRangeScale - gt; Degree, and PlotRange - gt; All.... In PAGE 40: ...Possible Values Meaning Apart Rational, All Partial fraction decomposition only applies to polynomials with real or rational coe cients Definition True, False Use the transform de nition if all else fails to nd the transform (does not apply to the inverse z or Laplace transforms) Dialogue False, True, All Ascending levels of justi cation Simplify True, False Apply SPSimplify to result Terms False or integer Number of terms in series expansion (False means none) TransformLookup list of rules Users can specify their own transform pairs, like {x[n] : gt; X[z]} or {y[t1,t2] : gt; Y[s1,s2]} Table1 2: Meaning of the Options for the Transform Rule Bases... In PAGE 41: ...Option Default Value CTFTransform Dialogue False Simplify True DFTransform Dialogue False InvDFTransform Dialogue False Terms False DTFTransform Dialogue False LaPlace Dialogue True Simplify True InvCTFTransform Apart Rational Dialogue False Simplify True Terms False InvDTFTransform Dialogue False Terms False InvLaPlace Apart Rational Dialogue True Simplify True Terms 10 InvZTransform Dialogue True Terms 10 ZTransform Dialogue True Table1 3: Options for the Transform Rule Bases. Definition always defaults to False and TransformLookup always defaults to an empty list.... ..."

### Table 7: On-line Pruning and Growing on 2-D Gabor Function. Number of Experts MSE

"... In PAGE 20: ... The initial network con guration again had 30 experts for the Gabor data set. Table7 shows results when the on-line structural adaptation algorithm was applied to the data set.... ..."

### Table 2. Sample stimuli used in the on-line cross-modal naming experiments.

"... In PAGE 7: ... Here we report only the sensitivity effects for the two populations (separately for grammatical, semantic and discourse items); these were calculated by subtracting the mean normalized response time (for all subjects from each population) for good continuations from the mean response times for bad continuations. Examples of the stimuli from each of the three constraint types (grammatical, semantic, and discourse) are shown Table2 . A detailed presentation of the methodology and the tasks can be found in Kempler et al.... In PAGE 8: ... Grammatical Constraints Forty grammatical sentences were constructed and then altered to create ungrammatical counterparts by the substitution, addition or deletion of one word. Two types of grammatical violations were included: (1) subject noun-verb agreement errors and (2) errors of transitivity (see Table2 ). Preliminary analysis of the subject-verb and transitive sentence structures did not demonstrate any effect due to construction type (F lt; 1), so the data from both constructions were combined for analysis.... In PAGE 8: ... In half of the sentences, the final word was grammatically and semantically appropriate. In the other half, the final word was anomalous due to a semantic (or pragmatic) violation ( Table2 ). The procedure and subject populations were identical to the grammatical experiment described above.... In PAGE 11: ... Andersen, 1998). Short subject-verb agreement stimuli were taken from the subject-verb agreement items described above ( Table2 ) and long stimuli were constructed by adding an intervening 10-15 word clause between the subject and the verb. For instance, the subject-verb agreement item The young girl was/*were was transformed into a longer item The young girl, who improved greatly every day because of the excellent teaching and good books was/*were.... In PAGE 13: ... This is also true for the on-line discourse items: in order to determine whether the pronoun him or them was coherent in the discourse, patients would have to understand the entire discourse. However, full processing of the sentences was not necessary for the on-line grammar and semantic items: in the case of our on-line grammatical and semantic items ( Table2 ), patients could perform well on the task (i.... In PAGE 15: ...asks. We also do not think that on-line tasks are inherently preferable. For example, we suspect that our on-line cross-modal naming task may be very unnatural, insofar as it requires substantially less processing than normal language comprehension. That is, in the case of our short grammatical and semantic items in the on-line experiments ( Table2 ), patients could perform well on the task by attending to only minimal information in the sentence concerning the relationship between verbs and nouns. As stated in the body of this chapter, simple grammatical relations (e.... ..."

### Table 1: On-line computational cost of the congruence transformation across a revolute joint.

1995

"... In PAGE 7: ... The result of the z-axial congruence transformation is used in the x-axial transformation which has exactly the same form. Table1 lists the nine steps that are identi ed in each axial screw congruence transformation which leads to a particularly e cient procedure. This approach is di erent from previous approaches for transformation of spatial (and Composite Rigid-Body) inertia matrices by Lilly and Orin [4] and re ected AB inertia matrices in both the rst draft of this paper and the work of Brandl, Johanni, and Otter [2].... In PAGE 7: ... Then only successive planar rotations were applied to the terms of the form, RT NR, to achieve a certain level of e ciency. At rst this seems more e cient since it results in only one set of nine steps from Table1 . However, it leads to more computation because iRi?1 and i?1pi are much more complex than that of either Rz; i and pz or Rx; i and px in the successive axial screw approach developed in this paper.... In PAGE 11: ... (13). To accomplish this, the results of Steps Bz, Fz, and Gz must be added together as shown in Table1 : Bz + Fz + Gz + GT z . The resulting matrix, Nz 11, is symmetric with a zero row and column (the third); therefore, the three upper triangular elements of the result are needed.... In PAGE 14: ... This step nishes the computation required for the upper left 3 3 block of the complete congruence transformation. To accomplish this, the results of Steps Bx, Fx, and Gx must be added together as shown in Table1 . The resulting matrix is symmetric; therefore, only the six upper triangular elements of the result are needed.... ..."

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