18.1.3. Example Circuit

So, let us go to the example circuit now. So, this is the example we have discussed before, but our focus here or our discussion center it will be different. Namely, it will be as I said linearization of the circuit or you may say that linearization of the input to output transfer characteristic of the circuit. This circuit we have seen before, it contains the BJT NPN transistor and it is having a base bias with a voltage. It is also having a collector bias through this battery V_CC through this resistor R.

This chunk introduces the example circuit that illustrates linearization in circuits using a Bipolar Junction Transistor (BJT). The BJT circuit we are examining has a base bias voltage and a collector bias connected through a battery and a resistor. The focus of this discussion is to linearize the characteristics of the circuit in terms of its input-output relationship.

Think of the BJT as a valve in a water pipe. When you adjust the valve (the base voltage), it affects how much water (current) flows through the pipe (collector to emitter) based on the resistance of the pipe (the resistor). Just like small adjustments at the valve can create larger changes downstream, slight changes in input voltage can lead to significant variations in output voltage.

And, then if we vary this voltage V_BE, which is incidentally a V_BE voltage we may call this V_BE or V_BE whatever it is. So, if we vary this voltage it is expected that, if we retain rest of the thing same the voltage at the collector will change with this variation. This variation it is happening due to the base current variation, then the collector current variation, and then the I drop across this resistor R.

This chunk explains how variations in the base-emitter voltage (V_BE) affect the overall operation of the BJT circuit. By changing V_BE, we can control the base current, which in turn influences the collector current. The drop across the resistor (R) also contributes to the changes in the collector voltage. Thus, this highlights the relationship between the input (V_BE) and the output (collector voltage).

Imagine adjusting the brightness of a lamp using a dimmer switch. The dimmer switch's position corresponds to V_BE, and the brightness level is akin to the collector voltage. Just as small changes in the dimmer affect the light output proportionally, adjusting V_BE slightly will lead to measurable changes in the collector voltage.

So, then if I consider that we consider this is input and this is the corresponding output, then we do get input to output transfer characteristics. So, that we have discussed. For a given value of V_BE, we have drawn the transistor characteristic, namely the I versus V characteristic, and then also V_ce characteristic.

In this chunk, we look into how to express the relationship between input (V_BE) and output (collector voltage) by plotting the input-output transfer characteristic. This involves understanding the key characteristics of the transistor, including how the collector current is related to base current and how these can be graphed to visualize their interactions.

Imagine you're in a car, and the speedometer reflects how hard you press the gas pedal (input). This relationship can be plotted to show how pressing the gas pedal more increases the speed of the car (output). Similarly, plotting V_BE against collector voltage gives us a visual interpretation of our circuit's response.

So, if I just ask you to remember or recall whatever the discussion we are having. So, if we change this V_BE with respect to some point and then the current is going up or down; so, here if we vary this input or V_BE then the corresponding characteristic curve it is going up or down. And, accordingly the intersection point is also changing and that gives us the variation of the output voltage.

This chunk discusses the effect of varying V_BE on the input-output characteristic curves. It emphasizes the non-linear nature of these curves and how they will change with variations in the input voltage. This understanding is crucial for linearizing non-linear characteristics, where the focus will be on a narrow band of input values to simplify analysis.

Think of drawing a hilly path on a map. If you focus on a small section of the hill (narrow range of input voltages), the path looks straight. However, as you zoom out, the curve reveals its true non-linear nature. This concept is similar to how we linearize the curve around an operating point to simplify our electrical analysis.

So, we say that is fairly linear, but even then if you further zoom here and if you are trying to observe the exact characteristic, it will be compared to this non-linear part it will be linear, but then again depending on the range you are considering there will be non-linear part. Mainly, because you may recall that this part it appears to be linear, but this part it is having exponential dependency. By the way here in this case we have assumed that this early voltage it is very high and that is why we are considering this is flat.

In this chunk, we address the importance of the operating point, or Q-point, when analyzing the input to output characteristics. The Q-point allows for a better approximation of linear behavior over a limited input range, facilitating easier calculations. The discussion also notes potential non-linearities that may still affect the overall characteristic.

Consider a music volume control. If your sound system operates best within a specific volume level (Q-point), you will hear clear sound. If you go too low (exceeding the linear range), the music may sound distorted. This is similar to finding a suitable Q-point where the transistor operates effectively.

So, whenever we are talking about linearization is basically linearization of the input to output transfer characteristic with respect to Q-point. So, whenever we are talking about linearization is basically extracting the meaningful part of the non-linear characteristic.

This final chunk emphasizes that linearization involves taking non-linear characteristics and narrowing the focus to the Q-point, where the characteristics can be approximated as linear for analysis. This simplification allows for easier calculations and understanding of the circuit behavior in operation.

Imagine you're in a room full of chatter and want to focus only on one person speaking (Q-point). By tuning out all the other noise (non-linear parts), you can ensure you're hearing meaningful information. Linearization allows engineers to focus on the most usable data in a circuit's performance.

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