Cristian Ferent

Symbolic Matching and Constraint Generation for Systematic Comparison of Analog Circuits

This paper proposes an automated technique for systematically generating comparison data between two analog circuits. The comparison data presents the similar and distinguishing performance characteristics of the circuits with respect to DC-gain, bandwidth, common-mode rejection ratio, noise, and sensitivity. The comparison data is important for getting insight into the common and unique benefits of a circuit, selecting fitting circuit topologies for system design, and refining and optimizing circuit topologies. The technique utilizes matching of the topologies and symbolic expressions of the compared circuits to find the nodes with similar electric behavior. The impact on performance of the unmatched nodes is used to express the differentiating characteristics of the circuits. Experiments illustrate the technique for a pair of analog circuit designs.

Analog Circuit Design Knowledge Mining: Discovering Topological Similarities and Uncovering Design Reasoning Strategies

Mining engineering metaknowledge from electronic documents is important in devising new design solutions for emerging applications as well as in identifying new business opportunities. Continuously and comprehensively reviewing and assessing the entire technical literature to find the most relevant ideas and solutions is cumbersome as engineering innovations are constantly being proposed. In particular, high performance analog circuit design has been at the forefront of technological innovations given their importance in applications, like telecommunications, mobile applications, and health care. This paper proposes a model and mining techniques for representing analog circuit design metaknowledge. The metaknowledge representation includes three components: an associative component presenting the conceptual hierarchy of the considered circuits, a component expressing the performance capabilities (e.g., tradeoffs and bottlenecks) of the circuits, and a causal modeling part describing the more likely starting ideas and design plans used to create a circuit. Knowledge structures can be used to tackle new applications, identify opportunities to improve existing circuits, and validate design correctness. A case study illustrates the proposed knowledge structure for a set of 30 modern, high-frequency analog circuits.

An axiomatic model for concept structure description and its application to circuit design

This paper describes an axiomatic model to express concept structures in analog circuit design. The concepts of a structure represent sets of circuit designs, and are defined based on the similarities and differences in their circuit topology, behavior and performance. Similarities and differences are found through concept matching, a main operator of the concept structure. A concept structure is extended with new concepts that are created by combining the features of existing concepts and by exploring new relations between variables through instantiation. Concepts are characterized by a set of metrics, e.g., variety, utility, novelty, complexity, flexibility, constraining factor, and bottleneck. The paper presents a novel circuit design methodology as an application of the model. Two case studies illustrate the utility of the axiomatic model in expressing knowledge structures for various types of circuits.

Measuring the uniqueness and variety of analog circuit design features

Analog circuit design activity is currently a less formalized process, in which the main source for innovation is the designers ability to produce new designs by combining basic devices, sub-circuits, and ideas from similar solutions. There are few systematic methods that can fuse and transform the useful features of the existing designs into new solutions. Moreover, most automated circuit synthesis tools are still limited to routine tasks, like transistor sizing and layout design. Developing new design techniques that can combine the existing design features requires metrics that describe the uniqueness and variety of the features. This paper evaluates for analog circuits two such general-purpose metrics proposed in [1,2]. Three case studies are discussed on using the metrics to characterize the design features of current mirrors, transconductors, and operational amplifiers. The two metrics and the presented study is useful in producing an overall characterization of analog circuit features. This can help in enhancing the circuit design process, training of young designers, and developing new automated synthesis tools that can explore more solution space regions that are likely to include novel design features.

Analog circuit design space description based on ordered clustering of feature uniqueness and similarity

This paper presents a symbolic technique to create ordered feature clustering schemes that express the main similarities and differences between analog circuits. Four separation scores, based on entropy, item characteristics, category characteristics, and Bayesian classifiers, were studied to produce clustering schemes that offer insight about the uniqueness and importance of specific design features in setting AC performance as well as the limiting factors of the designs. The experiments consider a set of 50 state-of-the-art amplifier circuits. The paper offers a detailed discussion on using the insight obtained from circuit feature clustering for topology synthesis and refinement.

A symbolic technique for automated characterization of the uniqueness and similarity of analog circuit design features

This paper presents a technique for automated generation of hierarchical classification schemes to express the main similarities and differences between analog circuits. The produced classification schemes offer insight about the uniqueness and importance of specific design features in setting various performance attributes as well as the limiting factors of designs. Hence, the classification schemes serve as a systematic way of relating one circuit design to alternatives. The automatically produced classification schemes for a set of OpAmps are discussed.

Hierarchical approach for intelligent lighting control in future urban environments

This paper proposes a novel concept and the related architecture for scalable and flexible lighting control in cities. The goal is to minimize the overall energy consumption without affecting safety. We are proposing a two-level control strategy based on qualitative processing. The lower level Zone Lighting Coordination Unit adjusts the lighting intensity of each lamp post through fuzzy logic. The parameters of the fuzzy controller are set by the upper level Lighting Coordination Unit, which uses a knowledge based mechanism. A case study illustrates the two-level control concept.

A prototype framework for conceptual design of novel analog circuits

This paper presents a reasoning-based synthesis method to design novel analog circuits. In addition to producing circuit topologies and constraints characterizing the topologies, the method finds alternative signal processing flows which represent different conceptual designs that can meet the specification requirements. Each synthesis step aims to remove a design bottleneck by changing the trade-off expressions that link the variables of the trade-off. The main steps of the synthesis method are also illustrated in the paper.

Systematic comparison of two low-voltage amplifiers using topology matching and performance constraints

This paper presents the comparison of two low-voltage amplifiers using a systematic, two step procedure: (i) automated topological matching highlighting common and different signal path structures and symbolic expressions and (ii) constraint extraction and analysis illustrating how dissimilarities between circuits impact relevant performance and showing design flexibility with respect to trade-offs. The obtained comparison is important for understanding benefits and limitations of unique features in designs, for selecting better fitting topologies, and for analog circuit synthesis tools.

Novel circuit topology synthesis method using circuit feature mining and symbolic comparison

This paper presents a reasoning-based approach to analog circuit synthesis using ordered node clustering representations (ONCR) to describe alternative circuit features and symbolic circuit comparison to characterize performance tradeoffs of synthesized solutions. Case studies illustrate application of the proposed methods to topology selection and refinement.