A note on RNS architectures for the implementation of the diagonal function

2015 ◽  
Vol 115 (4) ◽  
pp. 453-457 ◽  
Author(s):  
Stanisław J. Piestrak
Keyword(s):  
Author(s):  
Raymond M. Smullyan

§1. Some Preliminary Theorems. we continue to let S be an arbitrary system, P be the set of Gödel numbers of the provable formulas of S and R be the set of Gödel numbers of the refutable formulas of S. Theorem 1. The set P̃* is not representable in S. Proof. This is the diagonal argument all over again. If H(v1) represents P̃* and h is the Gödel number of H(v1), the H[h̅] is provable in S iff h Ï p* iff d(h) ÏP iff H[h̅] is not provable in S, which is a contradiction. Theorem 1.1. If S is consistent, then P* is not definable in S. Proof. Suppose P* is definable in S. If S were consistent, then P* would be completely representable in S (cf. §3.1, Ch. 0). Hence P̃* would be representable in S, contrary to Theorem 1. Therefore, if S is consistent, then P* is not definable in S. Theorem 1.2. If the diagonal function d(x) is strongly definable in S and S is consistent, then P is not definable in S. Proof. Suppose d(x) is strongly definable in S. Since P* = d -1(P), then if P were definable in S, P* would be definable in S (by Th. 11.2, Ch. 0). Hence S would be inconsistent by Theorem 1.1. Exercise 1. Show that if S is consistent, then R* is not definable in S. Exercise 2. Show that if S is consistent, then no superset of R* disjoint from P* is definable in S, and no superset of P* disjoint from R* is definable in S. Exercise 3. Prove that if S is consistent and if the diagonal function is strongly definable in S, then no superset of P disjoint from R is definable in S. [This is stronger than Theorem 1.2.] §2. Undecidable Systems. A system S is said to be decidable (or to admit of a decision procedure) if the set P of Gödel numbers of the provable formulas of S is a recursive set. It is undecidable if P is not recursive. This meaning of ‘undecidable’ should not be confused with the meaning of ‘undecidable’ when applied to a particular formula (as being undecidable in a given system S).


2019 ◽  
Vol 124 (1) ◽  
pp. 81-101
Author(s):  
Manfred Stoll

In the paper we characterize the reproducing kernel $\mathcal {K}_{n,h}$ for the Hardy space $\mathcal {H}^2$ of hyperbolic harmonic functions on the unit ball $\mathbb {B}$ in $\mathbb {R}^n$. Specifically we prove that \[ \mathcal {K}_{n,h}(x,y) = \sum _{\alpha =0}^\infty S_{n,\alpha }(\lvert x\rvert )S_{n,\alpha }(\lvert y\rvert ) Z_\alpha (x,y), \] where the series converges absolutely and uniformly on $K\times \mathbb {B}$ for every compact subset $K$ of $\mathbb {B}$. In the above, $S_{n,\alpha }$ is a hypergeometric function and $Z_\alpha $ is the reproducing kernel of the space of spherical harmonics of degree α. In the paper we prove that \[ 0\le \mathcal K_{n,h}(x,y) \le \frac {C_n}{(1-2\langle x,y\rangle + \lvert x \rvert^2 \lvert y \rvert^2)^{n-1}}, \] where $C_n$ is a constant depending only on $n$. It is known that the diagonal function $\mathcal K_{n,h}(x,x)$ is a radial eigenfunction of the hyperbolic Laplacian $\varDelta_h $ on $\mathbb{B} $ with eigenvalue $\lambda _2 = 8(n-1)^2$. The result for $n=4$ provides motivation that leads to an explicit characterization of all radial eigenfunctions of $\varDelta_h $ on $\mathbb{B} $. Specifically, if $g$ is a radial eigenfunction of $\varDelta_h $ with eigenvalue $\lambda _\alpha = 4(n-1)^2\alpha (\alpha -1)$, then \[ g(r) = g(0) \frac {p_{n,\alpha }(r^2)}{(1-r^2)^{(\alpha -1)(n-1)}}, \] where $p_{n,\alpha }$ is again a hypergeometric function. If α is an integer, then $p_{n,\alpha }(r^2)$ is a polynomial of degree $2(\alpha -1)(n-1)$.


2000 ◽  
Vol 73 (5-6) ◽  
pp. 189-198 ◽  
Author(s):  
G. Dimauro ◽  
S. Impedovo ◽  
G. Pirlo ◽  
A. Salzo
Keyword(s):  

2016 ◽  
Vol 3 (2) ◽  
pp. 49-52
Author(s):  
Yogesh Kumar Gupta ◽  
V. H. Badshah ◽  
Mamta Singh ◽  
Kiran Sisodiya

2020 ◽  
Vol 7 (1) ◽  
pp. 1788298
Author(s):  
A. O. Isere
Keyword(s):  

2008 ◽  
Vol 69 (9) ◽  
pp. 2851-2856 ◽  
Author(s):  
R. Mesiar ◽  
A. Mesiarová-Zemánková
Keyword(s):  

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1784
Author(s):  
Mikhail Babenko ◽  
Maxim Deryabin ◽  
Stanislaw J. Piestrak ◽  
Piotr Patronik ◽  
Nikolay Chervyakov ◽  
...  

Number comparison has long been recognized as one of the most fundamental non-modular arithmetic operations to be executed in a non-positional Residue Number System (RNS). In this paper, a new technique for designing comparators of RNS numbers represented in an arbitrary moduli set is presented. It is based on a newly introduced modified diagonal function, whose strictly monotonic properties make it possible to replace the cumbersome operations of finding the remainder of the division by a large and awkward number with significantly simpler computations involving only a power of 2 modulus. Comparators of numbers represented in sample RNSs composed of varying numbers of moduli and offering different dynamic ranges, designed using various methods, were synthesized for the 65 nm technology. The experimental results suggest that the new circuits enjoy a delay reduction ranging from over 11% to over 75% compared to the fastest circuits designed using existing methods. Moreover, it is achieved using less hardware, the reduction of which reaches over 41%, and is accompanied by significantly reduced power-consumption, which in several cases exceeds 100%. Therefore, it seems that the presented method leads to the design of the most efficient current hardware comparators of numbers represented using a general RNS moduli set.


Electronics ◽  
2019 ◽  
Vol 8 (6) ◽  
pp. 694 ◽  
Author(s):  
Maria Valueva ◽  
Georgii Valuev ◽  
Nataliya Semyonova ◽  
Pavel Lyakhov ◽  
Nikolay Chervyakov ◽  
...  

The residue number system (RNS) is a non-positional number system that allows one to perform addition and multiplication operations fast and in parallel. However, because the RNS is a non-positional number system, magnitude comparison of numbers in RNS form is impossible, so a division operation and an operation of reverse conversion into a positional form containing magnitude comparison operations are impossible too. Therefore, RNS has disadvantages in that some operations in RNS, such as reverse conversion into positional form, magnitude comparison, and division of numbers are problematic. One of the approaches to solve this problem is using the diagonal function (DF). In this paper, we propose a method of RNS construction with a convenient form of DF, which leads to the calculations modulo 2 n , 2 n − 1 or 2 n + 1 and allows us to design efficient hardware implementations. We constructed a hardware simulation of magnitude comparison and reverse conversion into a positional form using RNS with different moduli sets constructed by our proposed method, and used different approaches to perform magnitude comparison and reverse conversion: DF, Chinese remainder theorem (CRT) and CRT with fractional values (CRTf). Hardware modeling was performed on Xilinx Artix 7 xc7a200tfbg484-2 in Vivado 2016.3 and the strategy of synthesis was highly area optimized. The hardware simulation of magnitude comparison shows that, for three moduli, the proposed method allows us to reduce hardware resources by 5.98–49.72% in comparison with known methods. For the four moduli, the proposed method reduces delay by 4.92–21.95% and hardware costs by twice as much by comparison to known methods. A comparison of simulation results from the proposed moduli sets and balanced moduli sets shows that the use of these proposed moduli sets allows up to twice the reduction in circuit delay, although, in several cases, it requires more hardware resources than balanced moduli sets.


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