Abstract: Methods and apparatus for analyzing financial data generally includes a predictive modeling system. The predictive modeling system may include an artificial agent responsive to an input data set. The artificial agent may produce an estimated data set including a market conditions data set. The market conditions data may include an estimate of at least one of liquidity of a market, strategy of a counterparty, and an effect of information leakage. The artificial agent may determine a predictability value for the estimated data set. The predictive modeling system may also include an agent factory responsive to the input data set. The agent factory may generate an artificial agent in response to the input data set.

Abstract: Methods and apparatus for analyzing financial data generally includes a predictive modeling system. The predictive modeling system may include an artificial agent responsive to an input data set. The artificial agent may produce an estimated data set including a market conditions data set. The market conditions data may include an estimate of at least one of liquidity of a market, strategy of a counterparty, and an effect of information leakage. The artificial agent may determine a predictability value for the estimated data set. The predictive modeling system may also include an agent factory responsive to the input data set. The agent factory may generate an artificial agent in response to the input data set.

Abstract: Methods and apparatus for predictive analytics generally comprise one or more artificial agents and an agent factory. An artificial agent may be responsive to at least one of an internal data set and an external data set. Further, an artificial agent may produce a correlation data set relating an outcome data set and at least one of the internal data set and the external data set. In addition, an artificial agent may produce a predictability value corresponding to the correlation data set. The agent factory may be responsive to the outcome data set. Also, the agent factory may produce the artificial agent in response to the outcome data set.

Abstract: An RF transmitter provides both GSM and EDGE capability by implementing collector voltage control over the power transistor(s) in a power amplifier. During EDGE mode, linear base-biasing a power amplifier (PA) allows collector control to provide either saturated mode PA operation (during ramp up/ramp down) or linear mode PA operation (during data burst). Collector control can therefore be used to provide the accurate ramp up and ramp down profiles required for both GSM and EDGE burst output signals, and can also be used to set the level of the constant envelope data burst of a GSM burst output signal, while linear mode PA operation can provide the non-constant envelope EDGE data burst. A variable gain amplifier is used to adjust the input signal to the power amplifier such that the desired transmission level is achieved.