### Table 1: The table describes how binder cells of all the memorized bindings respond to a retrieval cue containing the three bindings hr1 = f1i, hr2 = f2i, and hr3 = f3i. The expected number of binder cells responding correctly are marked in boldface. Note that a vast majority of binder cells for any given binding respond correctly to the retrieval cue. Each row in the table describes the response of binder cells of a speci c binding. This response typi es the response of a whole class of binder cells. Thus the table completely characterizes the response of binder cells. This characterization holds irrespective of the number of bindings memorized. See text for details. 16

2001

"... In PAGE 17: ...ections and will be candidates for recruitment for a binding is 195.0173. 3. The expected number of binder cells of various bindings that will re in response to a retrieval cue containing the three bindings hr1 = f1i; hr2 = f2i, and hr3 = f3i (see Table1 ). As shown in Table 1, a vast majority of binder cells of any given binding respond correctly to the cue.... In PAGE 19: ... This response, however, typi es the response of a whole class of binder cells. Thus the data in Table1 speci es the response of binder cells of all the bindings memorized in bind prior to the posing of the retrieval cue. The response of hr1 = f1i binder cells typi es the response of binder cells of all bindings mentioned in the retrieval cue (this is indicated by the row label hreq = feqi which refers to all bindings of the form hri = fii, 1 i 3).... In PAGE 19: ... Finally, the response of hr10 = f10i binder cells typi es the response of binder cells of any binding involving roles and llers that do not appear in the retrieval cue (row label hrexc = fexci). Thus Table1 completely characterizes the response of binder cells. Note that this characterization holds irrespective of the number of bindings memorized in bind.... In PAGE 20: ...oss of only x% of the 195.0173 (expected) binder cells for a given binding. Thus the memorization of binding-detectors is robust with respect to di use cell loss. The quantities in Table1 are based on ltd = 0 (i.... ..."

Cited by 25

### Table 1: Estimates of instruction performance parameters for Blue Gene ISA. Each type of instruction is characterized by the number of cycles it keeps the execution unit busy (column execution ) and the latency for it to complete (column latency ).

2001

"... In PAGE 8: ... This value was validated by running the trace through the cache simulator. The performance parameters for the simulated architecture are shown in Table1 . These parameters are early estimates and may change when the low-level logic design is completed.... ..."

Cited by 15

### Table 1: Summarizing the characterization results

"... In PAGE 4: ... The results presented in this paper are listed below. Table1 summarizes the characterization results and compares them with previous results, showing how the set of drawable trees changes as changes. Columns of the table labelled \new quot; describe results of this paper; Columns labelled \previous quot; describe known results.... In PAGE 19: ... The proof is now completed by observing that inequalities 1 and 2 can be also obtained by applying Lemma 9 to a stable [ ]-drawing of T; thus if T does not admit a stable ( )-drawing, it does not admit a stable [ ]-drawing either. 2 5 Characterizing Representable Trees In this section we prove the correctness of the claims in Table1 . Much of the content of the Table is based on what we have presented in the previous sections, but other results are still necessary.... ..."

### Table 6: Static indices of the task graphs of the block multiplication and LU decomposition algorithms. Single-value indices are determined by executing an algorithm with a given number of proces- sors p. The average characteristics of the tasks (tcomp; tcomm) as well as those of the messages exchanged (nmessages; lmessages), and the global number of I/O operations nI=O op are particu- larly useful when the load of the algorithm must be reproduced (e.g., in simulation studies, in the evaluation of mapping and routing strategies). A more complete characterization of the behavior of parallel algorithms consists of plotting the metrics as a function of the number of available processors (signatures) or as the execution progresses (pro les) [41]. The global execution time T(p) of an algorithm, i.e., the execution signature [42], can be sub- divided into two components:

1993

Cited by 63

### Table (I) shows explicit expressions for the rst few of these polynomials. These polynomials are orthogonal in the sense that their inner product lt; j k gt;, which is de ned as the statistical average of their product, is equal to zero for j 6 = k. Moreover, they can be shown to form a complete basis in the space of second order random variables. A complete probabilistic characterization of the process S( ) is obtained once the deterministic coe cients Sj have been calculated. A given truncated series can be re ned along the random dimension either by adding more random variables to the set f ig or by increasing the maximum order of polynomials included in the Polynomial Chaos expansion. The

1998

Cited by 7

### Table II illustrates the power of using implications to approximate the set of reachable states, and it also shows a way to strengthen our results. In this work, the reachable state set is approximated by those states which satisfy a conjunction of implications. It is not obvious that such a conjunction could ever completely characterize the reachable state set. Furthermore, we only consider implications between nodes pre-existing in the design. A design may lack nodes conducive to implications, and this may limit our method. To test the effectiveness of using implications, we found the exact set of reachable states for the small benchmarks and then projected this set onto the set expressible as a conjunction of implications. If we have an expression R such that R = 1 iff the current state is reachable then we can project R onto the set expressible with implications by finding:

### Table 2: Characterizations of Types of Blocks

"... In PAGE 11: ... This led Batagelj (1997) and Doreian, Batagelj, and Ferligoj (1994) to the definition of several types of connection inside and between the clusters as different types of blocks. Some of them are presented in Table2 . From the definition of structural equivalence it follows that there are two basic blocks: null and complete (Batagelj, Ferligoj, and Doreian, 1992).... ..."

### Table 2: Network Characterization: Constraints

"... In PAGE 6: ... Thus, we have the following interference constraints for the general graph, where this distinction is made clear. X e02E(t(e))[E(h(e)) yt i(e0) 1; 8i 2 OC; 8e 2 E [ EI; 8t (4) Table2 lists these three constraints that characterize the MC-MR wireless network G. Each of these constraints char- acterize the channel, node and interference constraints re- spectively, and thus, equations (1), (2), and (4) are both necessary and su cient conditions to check for the feasibil- ity of a link schedule in the MC-MR network G.... In PAGE 7: ... A complete char- acterization of these forbidden subgraphs is not possible.6 However, the key point is to note that the ILP constraints in Table2 are both necessary and su cient for any net- work graph. The gap arises only due to relaxation of the integral constraints.... ..."

### Table 3 Argument completeness values concerning position -justification combinations.

"... In PAGE 3: ...rgument is non-complete. The expert defines the different degrees of argument completeness. The argument completeness, which is associated with the recognition or not of an instance of a cognitive category, is used as a vehicle to reveal the degree of the recognition or not of the corresponding cognitive category. Table3 demonstrates all possible combinations of position-justification pairs, the corresponding argument completeness and characterization and the degree of recognition of a cognitive category. Possible values of the argument completeness are: complete, almost complete, intermediate, nearly incomplete and incomplete.... ..."

### Table 1. Summary of results. NPCmeans that the problem is NP-complete.

1997

"... In PAGE 3: ... Since we can prove that it is NP-complete to decide whether a 2-connected planar graph of maximum degree 2 T ? 1 has a T -spanning tree, this result establishes a complete characterization of the T -spanning tree problem for k-connected planar graphs of maximum degree G. Table1 summarizes the results (it assumes that G gt; T 2). Organization of the paper Section 2 provides basic terminology.... ..."

Cited by 5