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Positive feedback source-coupled logic (PFSCL) is proposed as an alternative logic style to traditional SCL logic, which is often used in high-resolution mixed-signal integrated circuits. Positive feedback allows for significantly reducing the NMOS transistors' aspect ratio compared to traditional single-ended SCL gates for equal values of design constraints. The resulting reduction in NMOS parasitic capacitances permits a significant speed up, which can be traded off to achieve a power saving for a given speed constraint, as well as a silicon area reduction. PFSCL gates are analytically modeled in terms of their static parameters and delay, which are expressed as a function of bias current, transistors' aspect ratios and process parameters. Spectre simulations by using a 0.35-μm CMOS process confirm that the proposed models are sufficiently accurate in practical cases. PFSCL gates are also compared with traditional SCL circuits by resorting to two different metrics: the gate delay in a Ring Oscillator and that of an inverter with a fan-out of 4. The comparison confirms that PFSCL logic is faster than SCL logic in most cases, and design conditions leading to a speed advantage are identified. As a result, PFSCL gates are an interesting alternative to traditional SCL circuits in mixed-signal applications requiring a high speed or a good balance with power dissipation

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This paper considers a class of nonsymmetric cooperative neural networks (NNs) where the neurons are fully interconnected and the neuron activations are modeled by piecewise linear (PL) functions. The solution semiflow generated by cooperative PLNNs is monotone but, due to the horizontal segments in the neuron activations, is not eventually strongly monotone (ESM). The main result in this paper is that it is possible to prove a peculiar form of the LIMIT SET DICHOTOMY for this class of cooperative PLNNs. Such a form is slightly weaker than the standard form valid for ESM semiflows, but this notwithstanding it permits to establish a result on convergence analogous to that valid for ESM semiflows. Namely, for almost every choice of the initial conditions, each solution of a fully interconnected cooperative PLNN converges toward an equilibrium point, depending on the initial conditions, as + . From a methodological viewpoint, this paper extends some basic techniques and tools valid for ESM semiflows, in order that they can be applied to the monotone semiflows generated by the considered class of cooperative PLNNs.Index Terms-Convergence, cooperative neural networks, dynamical systems, limit set dichotomy, monotone and eventually strongly monotone semiflows.

The paper analyzes some fundamental properties of the solution semiflow of nonsymmetric cooperative standard (S) cellular neural networks (CNNs) with a typical three-segment piecewise-linear (pwl) neuron activation. Two relevant subclasses of SCNNs, corresponding to one-dimensional circular SCNNs with two-sided or single-sided positive interconnections between nearest neighboring neurons only, are considered. For these subclasses it is shown that the associated solution semiflow satisfies the fundamental properties of the CONVERGENCE CRITERION, the NONORDERING OF LIMIT SETS and the LIMIT SET DICHOTOMY, and that this is true although the semiflow is not eventually strongly monotone. As a consequence such CNNs are almost convergent, i.e., almost all solutions converge toward an equilibrium point as time tends to infinity. To the authors' knowledge the paper is the first rigorous investigation on the geometry of limit sets and convergence properties of cooperative SCNNs with a pwl neuron activation. All available convergence results in the literature indeed concern a modified cooperative CNN model where the original pwl activation of the SCNN model is replaced by a continuously differentiable strictly increasing sigmoid function. The main results in the paper are established by conducting a deep analysis of the properties of the omega-limit sets of the solution semiflow defined by the considered subclasses of SCNNs. In doing so the paper exploits and extends some mathematical tools for monotone systems in order that they can be applied to pwl vector fields that govern the dynamics of SCNNs. By using some transformations and referring to specific examples it is also shown that the treatment in the paper can be extended to other subclasses of SCNNs.