A sparse crossbar (n, m, e)-concentrator is a bipartite graph with n inputs and m outputs in which any c or fewer inputs can be matched with an equal number of outputs, where c is called its capacity. We present a number of new results on the crosspoint complexity of such concentrators. First, we describe a sparse crossbar (n, m, m)-concentrator whose crosspoint complexity matches Nakamura-Mass...

This paper develops a method to jointly estimate crop yield elasticities and area elasticities with respect to output prices based on a theoretically consistent model. The model uses a duality theory approach for the multi-output and multi-input firm, and introduces uncertainty in the level of target output which conditions the cost minimization problem, in the output prices and in the conditio...

Given measured data generated by a discrete-time linear system, we propose a model consisting of a linear time-invariant system affected by norm-bounded perturbation. Under mild assumptions, the plants belonging to the resulting uncertain family form a convex set. The approach depends on two key parameters: an a priori given bound of the perturbation and the input used to generate the data. It ...

Cryptographic hash functions reduce inputs of arbitrary or very large length to a short string of fixed length. All hash function designs start from a compression function with fixed length inputs. The compression function itself is designed from scratch, or derived from a block cipher or a permutation. The most common procedure to extend the domain of a compression function in order to obtain ...

Artificial neural networks built from two-state neurons are powerful computational substrates, whose computational ability is well understood by analogy with statistical mechanics. In this work, we introduce similar analogies in the context of spiking neurons in a fixed time window, where excitatory and inhibitory inputs drawn from a Poisson distribution play the role of temperature. For single...

I intend to use the streaming model as the basis for Admiral 2, particularly that of the StreamIt language [1]. In this model, a program consists of multiple independent filters, each of which consists of a steady-state function that computes a fixed number of outputs from a fixed number of inputs. These filters are composed hierarchically into a streaming graph, where edges correspond to the f...

The calculation of RTS amounts to measuring a relationship between inputs and outputs in a production structure. There are many methods to measure RTS in the primal space or the dual space. One of the main approaches is using the multiplier on the convexity constraint. But returns to scale measurements in DEA models are affected by the presence of regulatory constraints. These additional constr...

A dynamic scaling (DS) method is proposed as a cost-effective means of eliminating overflow and limit cycle oscillations in fixed-point direct-form recursive filters. It is implemented by adding a DS unit to a fixed-point on-line module without modifying latter. On-line modules consume inputs and produce outputs digit serially, most significant digit first. The DS method introduces a shared exp...